DEV Community: Ruchita_Varma

How to Restart a Pod using kubectl Command?

Ruchita_Varma — Mon, 30 Jan 2023 11:43:00 +0000

In this blog, we’ll discuss in detail about kubectl commands, explore different ways to restart a pod using this command and how it helps in cluster management.

The ‘Kubectl’ Command

‘kubectl’is a command-line tool for managing and interacting with a Kubernetes cluster. It allows you to deploy, inspect, and manage the state of your applications and resources within the cluster. kubectl provides a wide range of operations, including creating and updating deployment objects, managing cluster resources and logs, scaling deployments, and rolling back changes.

Some common kubectl logs commands include:

kubectl get- List resources.
kubectl describe- Show detailed information about a resource.
kubectl apply- Apply a configuration to a resource by filename or stdin.
kubectl create- Create a resource from a file or from stdin.
kubectl delete- Delete resources by filenames, resources and names, or by using the resources and label selector.

Significance of ‘Kubectl’ Command

‘kubectl’ is a crucial component of the Kubernetes ecosystem. kubectl commands are highly useful for carrying out a variety of tasks related to managing and interacting with a Kubernetes cluster. It mainly helps in:

-Cluster management: kubectl provides a simple and convenient way to manage the resources in a Kubernetes cluster, including pods, services, Kubernetes deployments, and other components.
-Application deployment: kubectl can be used to deploy, update, and manage the applications running on a Kubernetes cluster. It supports deployment strategies such as rolling updates and blue-green deployments.
-Resource management: kubectl allows you to manage the resources in a cluster, including scaling, updating, and deleting resources.
-Debugging and troubleshooting: kubectl provides various commands and options to help you debug problems with your cluster and its components, including pods, services, and deployments.
-Automation: kubectl can be easily integrated into scripts and automation workflows to manage your cluster in an automated and repeatable manner.

Overall, kubectl is a powerful tool that makes it easy to manage and interact with a Kubernetes cluster, making it a critical component for DevOps and cloud-native infrastructure teams.

_**[Good Read: Your Guide To Kubernetes Monitoring!]**_

Ways to Restart a Pod using ‘kubectl’ Command

There are a number of different ways to restart a pod using the ‘kubectl’ command. Read this to gain information on kubectl restart pod in Kubernetes.

1. Delete and recreate the pod:

kubectl delete pod

where is the name of the pod that you want to restart. The ‘kubectl delete pod’ command deletes the existing pod, and the Kubernetes cluster will automatically create a new one to replace it, effectively restarting the pod.

2. Scale the replicas down to 0 and back up to 1:

kubectl scale --replicas=0 deployment/
kubectl scale --replicas=1 deployment/

where is the name of the deployment that manages the pod. This method is useful when the pod is managed by a deployment.

3. Use rolling-update to restart a pod in a rolling manner:

kubectl rollout restart deployment/

where is the name of the deployment that manages the pod. This method is useful when you want to perform a rolling update and restart all the pods in the deployment one by one, without any downtime.

So, using these details on kubectl restart pod, you can easily restart a pod within your Kubernetes cluster.

Role of ‘kubectl’ in Cluster Management

The role of ‘kubectl’ in cluster management includes,

Deploying applications and managing their lifecycle.
Inspecting and managing cluster resources and their state.
Scaling deployments to handle increased traffic.
Updating and rolling back changes to deployments.
Debugging and troubleshooting cluster issues.
Managing network and storage resources.
Interacting with cluster API objects and performing administrative tasks.

Overall, ‘kubectl’ acts as a bridge between a user and the Kubernetes cluster, providing a convenient way to interact with and manage the cluster from the command line.

Managing Cluster was never so EASY!

Just like kubectl logs commands help teams to interact with Kubernetes cluster,BuildPiper helps in the complete management and deployment of Kubernetes clusters.

Being a Kubernetes management console allowing DevOps teams to operate a dynamic environment at scale, BuildPiper helps,

Achieve immediate and comprehensive visibility into all the cluster entities.
Gain and monitor accurate performance with deep insights.
Get insights into the health status of the pods and nodes within the cluster.
Integrate and set up infrastructure monitoring and log management tools with out-of-the-box product functionalities.
Enable further configuration of Kubernetes to make it ready for microservices consumption.

BuildPiper is the perfect Kubernetes management console that enables effective and hassle-free cluster management in combination with its other incredible functionalities that include Managed Microservices, Secure CI/CD Pipelines, Security, Compliance, & Observability, and much more!

Talk to our experts to discuss critical business scenarios and major Kubernetes challenges NOW!

How to Create a Dockerfile?

Ruchita_Varma — Fri, 27 Jan 2023 11:05:24 +0000

Docker is a powerful tool for creating, deploying, and running applications in containers. A Dockerfile is a script that contains instructions for building a Docker image. It is used to automate the process of creating a container image, so that developers can quickly and easily create, test, and deploy their applications.

Here, in this blog, we will know what is a Dockerfile, explore the basics of Dockerfiles, including the syntax and structure of a Dockerfile, know how to create a Dockerfile, how Dockerfile works, why Dockerfile is used and what is Dockerfile used for. Whether you're new to Docker or an experienced user, this blog will provide you with the knowledge and resources you need to effectively use Dockerfiles in your projects.

What is a Dockerfile?

A Dockerfile is a script that comprises a set of instructions and commands for building a Docker image. It consists of a series of commands, each of which corresponds to a command in the Docker command-line interface. The commands in a Dockerfile are executed in order, and they typically include instructions for setting up the environment, installing dependencies, copying application files, and configuring the application to run when the container is launched. Once a Dockerfile is created, it can be used to build an image using the docker build command, which creates a new container image that can be run using docker run.

How to create a Dockerfile?

After reading about what is Dockerfile, let’s now understand how to create one. A Dockerfile is a script that includes the steps for creating a Docker image. Here are the basic steps for writing a Dockerfile:

1. Start with a base image: The first instruction in the Dockerfile should be the ‘FROM’ command, which specifies the base image to use. This can be an official image from the Docker Hub, such as ‘FROM ubuntu’, or a custom image built by another developer.
2. Run commands: Use the ‘RUN’ command to execute commands in the container. These commands are used to install dependencies, configure the environment, and perform other setup tasks.
3. Copy files: Use the ‘COPY’ command to copy files from the host machine into the container. This can be used to copy the application code or other configuration files.
4. Set environment variables: Use the ‘ENV’ command to set environment variables that will be available in the container.
5. Expose ports: Use the ‘EXPOSE’ command to indicate which ports the container should listen on.
6. Set the default command: Use the ‘CMD’ command to specify the command that should be run when the container starts.
7. Build the image: To build the image, navigate to the directory where the Dockerfile is located and run the following command: ‘docker build -t ’. This will create an image with the specified name, and the dot at the end specifies the current directory as the build context.

Here is an example of a simple Dockerfile that creates an image for a basic web server running on port 80:

This Dockerfile uses the ‘FROM’ instruction to start with the latest version of Ubuntu as the base image. The ‘RUN’ instruction runs the command ‘apt-get update && apt-get install -y apache2’ to install the Apache web server. The ‘COPY’ instruction copies the ‘index.html’ file from the host machine to the ‘/var/www/html/’ directory inside the container. The ‘EXPOSE’ instruction tells Docker that the container will listen on port 80. Finally, the ‘CMD’ instruction runs the command ‘/usr/sbin/apache2ctl -D FOREGROUND’ to start the Apache web server.

[Good Read: Top 3 Docker Alternatives to Consider in 2023]

How Dockerfile works?

A Dockerfile is a text file that contains instructions for building a Docker image. It is used by the docker build command to create a new image, which can then be run as a container. The Dockerfile specifies the base image to use, any additional software to install, and any configuration changes to make. Each instruction in the Dockerfile creates a new layer in the image, allowing for efficient caching and versioning of the image. Once the image is built, it can be pushed to a registry such as Docker Hub, where it can be easily shared and reused. This is how Dockerfile works.

Why Dockerfile is used?

A Dockerfile is a script that comprises instructions for creating a Docker image. A Dockerfile is an important tool for developers because it allows them to create consistent, portable, and isolated environments for their applications, and makes it easy to collaborate and automate the development & deployment process. Here is how Dockerfile helpful and important for developers.

- Brings Automation: It allows developers to automate the process of creating a container image, which can be used to run software in a consistent and isolated environment.

- Reduces Dependencies: By using a Dockerfile, developers can ensure that their application runs the same way on their local machine, a test server, and in production. This can help to reduce issues with environment-specific configurations and dependencies and make it easier to share and collaborate on projects.

- Speeds up the Development Process: Additionally, using pre-built images from a container registry like Docker Hub can speed up the development process by eliminating the need to manually install dependencies.

These are some of the important reasons why Dockerfile is used.

What is Dockerfile used for?

Some of the key benefits of using a Dockerfile include and primary purposes.

- Portability: Docker containers are lightweight and portable, so they can run on any machine that has Docker installed. This makes it easy to move applications between different environments, such as from development to production.

- Isolation: Docker containers are isolated from each other and from the host system, which can help to reduce issues with conflicting dependencies and configurations. This makes it easier to run multiple applications on the same machine without them interfering with each other.

- Collaboration: Dockerfiles can be shared and used by other developers to build and run the same image, making it easy to collaborate on projects and share development environments.

- Automation: A Dockerfile can be automated using a Continuous Integration/Continuous Deployment (CI/CD) pipeline, which can help to speed up the development and deployment process.

Hope, after reading this, you now must have got enough clarity on what is Dockerfile used for.

What did we JUST READ?

In this blog, we delved into the world of Dockerfiles and the power they provide in automating the creation and deployment of containerized applications. We covered the basics of Dockerfile syntax and structure. Additionally, we highlighted some of the key commands and instructions that are commonly used in Dockerfiles, such as FROM, RUN, COPY, and ENV.

Overall, Dockerfiles are a crucial tool for any developer or DevOps engineer working with Docker. By understanding how to effectively use Dockerfiles, you can streamline your development and deployment process, and create more efficient and scalable applications.

Top 3 DevOps Monitoring Strategies

Ruchita_Varma — Sun, 01 Jan 2023 12:03:33 +0000

Monitoring in DevOps is inherently proactive, and as a result, it identifies security gaps and threat prevention opportunities to enhance application performance even before the bugs are visible. But this is possible only when DevOps monitoring strategy is effectively and successfully implemented.

Here’s how you can devise an efficacious DevOps monitoring strategy in a rapidly changing environment for your enterprise. In this blog, we’ve discussed 3 best practices in DevOps monitoring to help you understand

How to get started
What to monitor
Which tools to use for monitoring

Let’s Begin!

Identify Vulnerabilities

A vulnerability is a defect or flaw present in the software. Vulnerabilities can exist in application dependencies or operating system (OS) packages. Common vulnerabilities include buffer overflows, missing authentication for critical functions, missing data encryption and insecure interactions between various software components.

Vulnerabilities and undetected system issues can result in delayed releases and deployment failures. Vulnerabilities are mainly of two types:

Known Vulnerabilities: These are weaknesses or vulnerabilities in an application that are already known or identifiable via lists maintained by National Vulnerability Database (NVD).
Unidentified Vulnerabilities: These types of vulnerabilities are not known in advance. They occur due to insecure coding practices, insecure design, or insecure architecture in the application.

It is important for businesses to monitor these vulnerabilities and mitigate them within a refrained time limit. These vulnerabilities can be addressed in several ways such as by monitoring third-party dependencies, conducting regular secure code reviews, preparing a security checklist, guiding the software development teams about major security concerns, and hiring experienced security professionals.

[Good Read: Observability for Monitoring Microservices — Top 5 Ways!]

Enable User Activity Monitoring

User activity monitoring is the process of actively monitoring and tracking the behaviour of users across IT resources such as devices and networks within an organization. User activity monitoring can help mitigate malicious cyberattacks and potential threats to the system. It is necessary to track unusual requests, multiple login attempts or log-ins from unknown devices.

Monitoring user behaviour alerts and notifies security teams about unusual activities and unauthorized access. For instance, a developer attempts to access an admin account.

With an effective strategy for monitoring in DevOps, teams can immediately detect and investigate suspicious user activity. Enterprises can easily find out if their employees are uploading sensitive data to public clouds, utilizing non-approved services and applications, or involving in restricted activities while using company network or resources. User activity monitoring tools help in ensuring that employees do not misuse company's confidential information.

Choose the Right Monitoring Tools

Complementing a set of effective and healthy monitoring practices are advanced tools that align with the DevOps culture based in an organization. Selecting such tools requires attention to identifying and implementing monitoring tools. Additionally knowing developer tools of code repositories, continuous integration tools and deployment tools is also needed.

Choosing a monitoring tool that meets your business goals and requirements starts with an evaluation process. It mainly involves understanding the functionality of each tool and analyzing which tool is best suited for each type of monitoring.

The right monitoring tools in DevOps should be able to,

Provide a complete and real-time view of the status of applications, services, and infrastructure in the production environment.
Informs and alerts you about errors, bugs and issues even before going live, in a pre-production environment.
Renders complete visibility of application enabling teams to find the potential reasons for failure in deployments and delays in releases.

List of Monitoring Tools in DevOps

Some of the important monitoring tools in DevOps available in the market today:

Sensu
Prometheus
Kibana
Splunk
BuildPiper
Dynatrace
Librato

Before you Start

These were some of the best practices in DevOps monitoring. But before you start executing your monitoring strategy, you must set and measure DevOps monitoring goals. These goals will help your teams in knowing how well your DevOps monitoring strategies are working. It also helps them in getting detailed insights into how efficient your workflow is and how well your teams perform. You need to,

Track the duration of each sprint.
Record and analyze the rate at which bugs are identified, documented, and fixed.
Identify the ratio of expected-to-delivered features.
Know whether your team is able to meet the set deadlines.
Assess whether the team is following the DevOps approach effectively.

BuildPiper has recently emerged as a popular Microservices monitoring tool in the DevOps space. The platform renders complete visibility of the deployment status with in-depth reporting on the reasons for failure thus enabling a secured, quick and seamless Microservices deployment. With BuildPiper, DevOps teams can get complete visibility of the deployment status and the pod status after service deployment.

Contact our experts to know more about the other interesting features of this platform!

5 Best Use cases of DevOps Monitoring

Ruchita_Varma — Fri, 30 Dec 2022 12:33:57 +0000

With DevOps monitoring, teams can quickly identify issues and fix them in advance before they impact the application's performance. In addition, the process enables developers to shift left to earlier phases of development, reducing the cycles of production changes. Failures and issues can easily be detected and dealt with manually or automatically as required with better DevOps monitoring tools.

No doubt, monitoring in DevOps brings significant benefits to enterprises but only when it is effectively implemented. In this blog, we’ll talk about different use cases to extract maximum advantage from DevOps monitoring. Here are 5 best use cases of monitoring in DevOps that can help organizations to achieve desired outcomes with complete success. Take a look!

We’ll discuss these 5 DevOps use cases for effective monitoring of the system environment.

Monitoring Git Workflows
Distributed Tracing
Continuous Integration/Deployment Log
Configuration Management Changelogs
Code Instrumentation

Let’s discuss these in detail!

Monitoring Git Workflows
Monitoring Git Workflows can help development teams in gaining a better view of their application ecosystem. Let’s see how. When multiple developers work on the same project functionality, there are higher chances of recurring codebase conflicts. Git helps manage and resolve conflicts occurring within the Git workflows. These conflicts may occur during code commits and software rollback. Monitoring Git workflows enable teams to keep track of all conflicts that can hinder the development speed and cause issues.

Distributed Tracing
Distributed tracing is a process of tracking application requests as they flow from frontend devices to backend services and databases. DevOps & SRE teams can use distributed tracing to check and monitor requests that exhibit high latency or errors. Distributed Tracing is important for optimizing app performance and identifying bottlenecks. With Distributed tracing, teams can understand how applications interact with each other through APIs. This way it becomes easier to detect and repair issues.
Distributed Tracing Tools: Jaeger, Zipkin, New Relic and Dynatrace.

[Good Read: The 3 Pillars of Observability: Logs, Metrics and Traces]

Continuous Integration/Deployment Log
With the growing adoption of CI/CD pipelines in the development space, monitoring them is crucial for a healthy system. Lack of monitoring and production-level resiliency can lead to delayed release or even bring the delivery pipelines to a grinding halt.

-CI logs inform teams about the errors or issues in the code builds. Monitoring them ensures the identification of potential challenges in the build pipeline so that teams can address them in advance.
-CD logs deliver reports on the development pipeline’s overall system health and status. It helps to troubleshoot any failed deployments/rollbacks and also repair potential issues.

Configuration Management Changelogs
Configuration management changelogs offer insights into the system’s overall health and critical changes. The changelogs contain records of all changes made to configurable components or resources of the system. Monitoring these logs enables teams to,

Get an overview of changes made to the system –manual and automated
View unauthorized changes
To identify and repair damages

Code Instrumentation
Code instrumentation is the process of inserting code into an application that collects data about its performance and operations route. By monitoring the instrumentation results, teams can easily determine the efficiency of the DevOps practices and identify potential gaps that need urgent lookout and improvements. Code instrumentation helps to measure a product’s performance by diagnosing errors. It’s also important for detecting bugs and enhancing testing.

Integrate before you Start
So, these were some of the important DevOps use cases that your teams must look into before implementing a particular monitoring strategy. These use cases can help in effective and successful execution of DevOps monitoring strategy. The use of monitoring tools in DevOps makes your system proactive and enhances its performance. Technology teams can easily identify system errors in advance and remove bottlenecks.

There’s no doubt that DevOps monitoring is critical for maintaining system’s health and performance. DevOps monitoring tools and platforms can help DevOps & SRE teams to get updates on the real-time status of the system.

Packaged as an out-of-the-box and ready-to-use solution to manage Kubernetes and Microservices application delivery, BuildPiper can help your team in gaining complete observability and monitoring. Discover HOW! No doubt, the platform is one of the most powerful monitoring tools in DevOps available in the market today.

Explore other interesting features of this platform, schedule a demo NOW!

Issues in Kubernetes Cost Management!

Ruchita_Varma — Mon, 31 Oct 2022 14:10:11 +0000

Here are some critical issues faced while managing Kubernetes costs to reduce your cloud bill and forecast the IT spending of your business. Let’s read in detail about these issues occurring in Kubernetes cost management!

Kubernetes plays a vital role in the DevOps world. No doubt, the use of Kubernetes in software development and deployment is here to stay, because it simplifies the deployment, management, and scaling of applications. It solves container issues by providing an extensible, declarative platform that automates the management of containers for high availability, resiliency, and scale.

85% of IT leaders agree that Kubernetes is “extremely important,” “very important,” or “important” to cloud-native application strategies according to a Red Hat survey from 2021.

With its incredible pros, there are cons to managing Kubernetes costs. While you plan to optimize your business infrastructure for a high-quality end-user experience, all this can come with a hefty price tag. No matter, whether you’re on-prem, or in AWS, GCP, Azure, or any other Kubernetes-supported platform, cost will always be a problem. Getting those costs under control and monitoring them right is important.

So, let’s start by exploring the issues in Kubernetes cost management, here in this blog!

Overestimation of Resource Needs

Setting more resource limits than actually needed is one of the most common issues concerned with managing Kubernetes prices. Because enterprises and their teams prioritize performance over anything else, they choose to set resource requests and resource limits above what they think they’ll really need. This is to ensure best-in-class applications and a good end-user experience. In case, if engineering teams did the opposite then they might end up under-provisioning their resources. This is surely not good for both: the end users and the organization.

At the same time, guessing what resources the application or service will need is hard to predict, and sometimes impossible. In lieu of having accurate utilization metrics before the service has gone live, teams trying to be on the safer side make large resource requests. But, once it’s in production, these requests can be scaled down.

[Good Read: 3 Tools To Automate Your Kubernetes Cluster Deployment!]

Lack of Visibility

Clear visibility of the various spending on Kubernetes resources is a must to possess for DevOps teams in order to reduce and optimize Kubernetes costs. How can your teams manage costs if they don’t even know what costs exist, and where they’re coming from? Analyzing and monitoring Kubernetes costs may appear easy at first but as you dive into its in-depth, you’ll find it’s a difficult thing to execute, especially when infrastructure resources are so dynamic and change all the time.

You should be able to identify the real origin of Kubernetes prices and its resources. In Kubernetes, this visibility can be achieved by looking at clusters, nodes, namespaces, workloads, and pods. It’s important that comprehensive visibility is provided to teams and stakeholders with an accurate view of which resources are being used and how they’re being used.

Inadequate Tooling

Teams can not manage and monitor Kubernetes' costs without having the right tools in hand. No doubt, you can collect all of the data yourself and create the right solutions. But, it wouldn’t be easy to modify these solutions, if changes are required.

The point of using good tools is to design a standard process for gaining complete visibility of the cluster resources for effective Kubernetes cost analysis. The de facto approach is to use Kubernetes APIs to hook into infrastructure monitoring tools like Prometheus and Grafana to visualize and understand costs better.

This strategy works, but issues may arise while turning the metrics extracted from Prometheus into cost savings opportunities. This is a difficult process as each step has its own set of complexities, making it difficult for you to manage Kubernetes costs efficiently.

Manage your Kubernetes Costs

It’s important for teams to get complete visibility and detailed insights into the cluster resources such as pods and nodes, for Kubernetes cost analysis. You can choose a robust Kubernetes management platform like BuildPiper that helps teams in gaining comprehensive visibility of your Kubernetes resources for optimizing Kubernetes costs and reducing your cloud bills.

To explore other interesting features of this platform, contact us NOW!

Kubernetes Cost Monitoring: 3 Metrics You Must Track!

Ruchita_Varma — Mon, 31 Oct 2022 13:11:57 +0000

Cost visibility is the foremost and most critical step in managing and forecasting Kubernetes prices. Here are three important metrics that you need to track for monitoring Kubernetes costs and doing Kubernetes cost analysis. Let’s take a look!

A recent survey conducted by CNCF in collaboration with the FinOps foundation revealed an increase in Kubernetes-related bills across the board in 2021.

What can be seen from the survey, is that most respondents were unable to monitor, manage, or predict Kubernetes cost-effectively. Kubernetes workloads are dynamic in nature which poses a challenge when it comes to calculating the cost of resources utilized by applications correctly. No doubt, performing Kubernetes cost management and measuring costs accurately in Kubernetes environments is complex.

So, before you plan to splurge on a Kubernetes cost monitoring solution, make sure that it includes these three crucial metrics.

1. Daily Cloud Spend

Tracking the daily cloud spend helps in knowing whether your current cloud costs are compatible with your budget. To keep cloud expenses in check, you need to have all the data in hand to easily compute the daily or weekly expenses. The daily spend report can help teams in doing that which ultimately helps enterprises in effective Kubernetes cost management.

Example:Let’s consider you have fixed a monthly budget of $2,000. So checking the daily cloud expenses on cloud usage will help in knowing whether you’re running under the budget or at least in line with it. If your average daily spend is approx $90 (30 days x $90 = $2700), you’re likely to end up with a higher cloud bill than expected.

Another important benefit of keeping a daily record of cloud cost metrics is that it allows you to identify the main elements of the usage or spending. By analyzing the daily report, you can easily verify how much has been spent each day for the last two weeks and prevent expenditure on the cost that may lead to cloud waste.

[Good Read: Avoiding The Kubernetes Cost Trap!]

2. Cost Per Provisioned and Requested CPU

Another important metric that needs to be regularly tracked is the cost per provisioned CPU and requested CPU. But, why do you need this? By constantly comparing the number of requested vs. provisioned CPUs, you can discover this gap and calculate how much you’re actually spending per requested CPU. This would make the cost reporting more accurate.

If you’re running a Kubernetes cluster that hasn’t been optimized for cost, you will see a large difference between how much you’re provisioning and how much you’re actually requesting. You’ll find that you’re spending money on provisioned CPUs and request only a small amount of them.

Let’s illustrate this with an example:

Example: Your cost per provisioned CPU is $4. If they’re not cost-optimized, then there will be a waste of a lot of resources. As a result, your cost per requested CPU is $20. This means that you’re running your clusters for a price that is 5x higher than expected.

3. Historical Cost Allocation

Example: Supposedly, you get a cloud bill from the billing manager asking why the bill it’s so high. Just like other teams that use public cloud services, there are chances that your expenses went over budget. But how to find all the other reasons that made the cloud bill go so high?

This is where the historical cost allocation report comes into the picture and can make a huge difference in Kubernetes cost analysis. This report can save time spent on identifying the other factors responsible for the extra costs. By checking last month’s expenditure dashboard, you can instantly view the cost distribution between namespaces or workloads in terms of dollar spend.

From this dashboard, you can easily find out the workloads that are running and using a lot of money but not doing anything. These are the idle workloads that are considered to be the prime driver of cloud waste.

No matter, whether you are an experienced professional or someone who’s just starting his Kubernetes journey, you can’t afford to overlook the costs of running a Kubernetes cluster and related Kubernetes prices.

Final Words!

By now, you must have got the idea of the important cluster metrics that shouldn’t be ignored during Kubernetes cost monitoring. Teams can right-size their nodes and pods or use tools such as Kubecost or BuildPiper to get the complete visibility of their Kubernetes workloads to limit and optimize their Kubernetes cluster costs.

BuildPiper is a Kubernetes management platform that has the ability to keep a track of the cluster metrics and give a clear picture of what is exactly happening inside the cluster, providing a secure, reliable, and consistent user experience for easy and hassle-free Kubernetes deployment.

Get in touch with our technical team to discuss and seek assistance on your critical business scenarios NOW!

The 3 Pillars of Observability: Logs, Metrics and Traces!

Ruchita_Varma — Fri, 30 Sep 2022 14:55:14 +0000

Logs, Metrics and Traces give their individual perspectives on system performance. When analyzed together, they provide a complete picture of your infrastructure allowing teams to gain granular insights into the system health and performance. Read more about these three pillars of Observability: Logs, Metrics and Traces, here in this article!

There are many potential data sources for observing and checking the performance of applications or infrastructure. But for most observability use cases, three types of data and information matter the most: Logs, Metrics and Traces.

These data types play such a crucial role in measuring cloud-native observability that they're known as the Three Pillars of Observability. Each pillar provides a different and valuable perspective of the system resources.

When these data sources are combined and analyzed, teams can easily find out what's happening within its complex application environments. Let’s drill down to understanding these 3 pillars of observability one by one!

What are Logs?

Logs are files that record events, alerts and errors as they occur within a system. Most logs contain contextual information, such as the time an event occurred and which user or endpoint was associated with it.

For instance, a log file for a web server might include when the server started, requests it received from clients and how the server responded to those requests. It records information about each successful transaction that happened as well as errors such as failed connections to clients.

Logs are a pillar of observability devops because they keep a track record of all events, bugs and errors that occur during the lifecycle of software resources. Teams can get comprehensive information about the events and bugs from these logs.

Logs are Best For: If you want to know when a problem occurred in the system, or which events or trends correlate with it, logs are an excellent source of visibility.

What are Metrics?

Metrics are quantifiable measurements that display the complete health and performance of applications or infrastructure. For instance, application metrics might track how many transactions an application handles per second, while infrastructure metrics measure how many CPU or memory resources are consumed on a server.

The main advantage of metrics is that they provide real-time insights into the state of resources. By correlating metrics with aggregated data from logs and traces, teams gain a thorough understanding and detailed insight into the system’s performance for identifying potential issues. This is why metrics are an important part of Observability devops.

Metrics are Best For: If you want to know how responsive your application is or detect anomalies that could be early signs of a performance issue, metrics are a key source of visibility.

What are Traces?

A distributed trace is the data that tracks the path of an application request as it flows through the various parts of an application. Trace records how long it takes each application component to process each request and transfer the result to the next component.

Traces help in identifying which parts of the application can trigger an error in advance. Teams may be able to know that a problem exists but it's difficult to find out the actual source of the problem in microservices environments without running traces.

Traces are Best For: If you need to find the root cause of any problem, distributed traces are the most effective way to accomplish this.

Summing it ALL!

If you want to observe cloud-native environments, then you need to start by collecting and analyzing logs, metrics and traces. It’s true that these aren't the only potential sources of observability, but they are the most important ones, which is what makes them the 3 pillars of observability.

Logs: A record of what’s happening within the software.
Metrics: An analysis of application performance and resource utilization.
Traces: How executions take place between the processes.

While focusing on building and scaling the product right, DevOps teams can rely on BuildPiper- as an underlying DevSecOps Platform for gaining complete Observability & Monitoring!

To explore its other interesting features, schedule a demo today!

You can read more about monitoring, observability, and the difference between the two here in this article!

Observability vs Monitoring Microservices- What’s all the BUZZ about?

Challenges of Monitoring Microservices!

Ruchita_Varma — Fri, 30 Sep 2022 14:35:00 +0000

Monitoring microservices is crucial for understanding how apps are functioning and identifying issues to prevent system failures in advance. Let’s take a look at some of the major microservices monitoring challenges here!

With Microservices architecture becoming the de facto standard for web applications now, constant monitoring, effective debugging and anomaly detection has become quite important. But, as monolithic applications become distributed across microservices and software teams facing pressures while shipping new features and experiences, it becomes extremely challenging to understand performance and identify issues & bottlenecks.

Here are some of the challenges your team might face during monitoring of microservices, here in this blog! Let’s take a look!

1. Microservices instead of a Monolith!

By adopting a microservice architecture, a typical monolith application is broken into individual components. Each of these components run their own programming language and database being deployed, scaled and upgraded independently.

Uber reported in late 2014, with 4,000 proprietary microservices and a growing number of open source systems that needed to be monitored, posed a challenge for monitoring their complex microservices system.

The Real Challenge: An increase in the number of discrete components you need to monitor makes it difficult to manage the system.

2. Cloud Native Architecture and Kubernetes!

Cloud Native architectures, based on containers and Kubernetes, are popularly being used for running microservices. But its widespread growth has augmented complexity in the process of monitoring of microservices. With cloud-native architecture and Kubernetes, teams need to monitor applications spanning multiple containers, pods, and namespaces, potentially over fleets of clusters.

Besides this, the container’s framework adds to the monitoring task as it becomes a crucial part of the system. Teams now need to monitor Kubernetes cluster metrics, node metrics, pod, and container metrics, as well as Kubernetes’ own control plane services.

The Real Challenge: In containerized workloads, DevOps & SRE teams have to monitor multiple layers and dimensions including infrastructure metrics, Kubernetes & containers metrics and application metrics.

3. Integrations with Open-Source and Cloud Services!

While implementing Microservices architecture, there arises a need for integration with Open-source and cloud services. This increases the use of built-in libraries, tools, and frameworks for building software systems, including web servers, databases, and queues. Monitoring microservices architecture consisting of these libraries and multiple third-party frameworks, makes it difficult to monitor microservices.

The Real Challenge: Complex integrations with a large and dynamic ecosystem of third-party platforms makes monitoring a daunting and time-consuming task for teams.

Key Takeaway

It’s crucial that DevOps & SRE need to continuously examine the gathered data to find solutions for problems within the app. Also, enterprises must invest and try exploring effective Microservices monitoring tools and practices to overcome these microservices monitoring challenges and get complete observability of the health status and performance of their business applications.

BuildPiper, a popular Microservices monitoring tool, renders complete visibility of the deployment status with in-depth reporting on the reasons for failure, enabling a secured, quick and seamless Microservices deployment. With BuildPiper, DevOps teams can get complete visibility of the deployment status and the pod status after service deployment.

To explore its other interesting features, schedule a demo today!

You can read more about monitoring, observability, and the difference between the two here in this article!

Observability vs Monitoring Microservices- What’s all the BUZZ about?

How do API Gateways Work?

Ruchita_Varma — Mon, 29 Aug 2022 18:27:07 +0000

API Gateway is a vital component of the Microservices architecture. An API gateway is a software pattern that is placed in front of an application programming interface (API) or group of microservices, to facilitate incoming requests and outgoing delivery of data and services. Read about API Gateway, its benefits and how it works, here in this API Gateway documentation!

What is an API Gateway?

What’s the real API Gateway meaning? An API gateway is an API management tool that exists between a client and a collection of backend services. An API gateway acts as a reverse proxy to accept all application programming interface (API) calls, aggregate the various services required to fulfil the requests and then return the appropriate result.

The Main Function of an API Gateway!

An API gateway that takes an application user’s request, routes it to one or more backend services, gathers the appropriate data and delivers it to the user in a single, combined package. It also provides analytics, protection against threats and other security for the application.

The primary role of an API Gateway is to act as a single entry point and standardized process for interactions between an organization's apps, data and services and internal and external customers.

How does an API Gateway work?

APIs allow separate applications to communicate with each other and exchange data within and outside the architecture. The API gateway provides a central focal point and standard interface to perform these exchange activities. It receives requests from internal and external sources, called "API calls," and packages these multiple requests, routes them to the appropriate API or APIs, and then receives and delivers the responses to the particular user or device that made the request.

Functions that are handled by API Gateways!

Other important functions related to Microservices that API gateways often handle include,

Protocol translation
Service discovery for identifying the location of service instances.
Building basic business logic within each service
Authentication and security policy enforcements
Stabilization and load balancing
Cache management
Monitoring, logging and analytics_

Benefits of using API Gateways!

After reading about API Gateway meaning, now let's read about its benefits. API Gateways are essential to a microservice architecture. Some of the benefits of using API Gateways include,

An API Gateway authenticates all traffic before routing it to the target service. It can perform self-authentication itself or use external authentication providers to accomplish the task.
An API Gateway can provide a service registry that keeps a record of all available service instances.
An API Gateway can protect services from spikes or DDoS attacks.
An API gateway has the ability to collect metrics, logs, and traces about all inbound traffic passing through it.

Caveats of using API Gateways!

This API Gateway documentation would be incomplete without discussing the key caveats that you must bear in mind before adding it to your applications. An API Gateway can enhance your microservice-based application with capabilities such as authentication, traffic management, load balancing, threat protection, and observability. If not properly configured, it can shut down the entire application. So, before adding it to your application architecture, your team must do a proper analysis of the app features and the real problem that it needs to address!

But, it’s not as simple as it looks so, managing microservices is in itself a demanding and difficult task. Monitoring, maintaining and deploying Microservices is undoubtedly a tough row to hoe! Adopting a powerful microservices management platform such as BuildPiper, packaged with incredible functionalities, can be a great option to go for!

Consult our tech experts to get immediate assistance on your critical business scenarios NOW!

5 Key Components of Microservices Architecture!

5 Business Pain Points that can be solved using DevSecOps tools!

Ruchita_Varma — Sun, 21 Aug 2022 18:00:00 +0000

As cyberattacks continue to rise in the industry today, businesses have begun to invest in DevSecOps tools and practices to ensure that their applications are secure. Here are 5 pain points that can be solved using the DevOps security tools and practices. Let’s read further to know about these concerns!

The Growth of DevSecOps!

With more companies realizing the importance of integrating security into their DevOps pipelines, the demand for DevOps security tools and products can be been growing strongly.

DevSecOps Market size was valued at USD 3.73 Billion in 2021 and is projected to reach USD 41.66 Billion by 2030, growing at a CAGR of 30.76% from 2022 to 2030, says a report.

Business Pain Points that You can Solve with DevSecOps!

The DevSecOps or the DevOps security methodology enables organizations to be more agile and adapt to ever-changing market trends. The ability to quickly deliver software helps enterprises stay ahead of their competition and that too while reducing the risk of data breaches, cyberattacks and malware.

Discussed below are five business pain points you can solve implementing the DevOps security approach. Let’s get started!

- Low-Security Level
Right from day one and throughout the entire SDLC, the development teams review, scan and test the code to identify even minor security problems. Moreover, DevSecOps enhances the communication between all the different teams. This contributes in identifying and nailing system issues & vulnerabilities thus making the entire infrastructure secured and robust.

- High Operational Costs
DevSecOps or introducing the DevOps security practice allows teams to detect bugs in the early stages of the development cycle (SDLC). By implementing continuous monitoring, DevOps teams can identify glitches before the software is deployed, ultimately decreasing the price of eliminating them substantially.

- Slowed-down Software Rollout
After integrating security practices into the development stages, the delivery pace increases. All thanks to the DevSecOps approach! At times, the development teams fail to detect the issues in the early stages due to which the software rollout may get delayed. But with the DevSecOps approach, teams can spot and identify issues before deployment at an advanced stage. This helps teams in getting rid of massive delays and enables them to focus more on the developed features.

- Lack of Compliance with International Regulations
There are certain industry standards like GDPR or PCI DSS which demand utmost consideration for handling data processing and protecting sensitive user information. Taking this into consideration, DevSecOps helps the teams to design software in such a way that meets all critical data security requirements.

-Time-Consuming Manual Security tasks
Automated security testing is a key element of any security solution. By removing the need for development, operations, and security team members to perform manual security tasks – not all, of course, but relatively simple trivial tasks such as code auditing and scanning – the DevSecOps approach helps pace up the delivery rates and gives team members enough time to innovate in areas where they excel the most.

On top of this, automated DevOps security tools help flag potential security risks early. This way security is seen as less of a rushed, last-minute inclusion and more of an component that is just as crucial as any other aspect of an application.

BuildPiper- The BEST WAY OUT!

While focusing on building and scaling the product right, DevOps teams can rely on BuildPiper - as an underlying DevSecOps Platform! With deeply-ingrained capabilities such as Managed Kubernetes, Managed Microservices, easily configurable CI/CD Pipelines, Security, Observability & Compliance - BuildPiper is one of the Most Powerful Microservices Delivery Platform and Reliable DevSecOps tools available in the industry TODAY!!

Read here to know why businesses can on this platform for security, scalability and reliability.

Read here to know why businesses can on this platform for security, scalability and reliability.

What makes BuildPiper the most sought-after DevSecOps Platform for Managing Microservices?

Schedule a demo today, to explore its other interesting features!

How to Describe a Helm Chart?

Ruchita_Varma — Wed, 06 Jul 2022 13:40:26 +0000

There is a definite format that you need to follow while creating a Helm Chart. Here’s how you can describe a Helm Chart specifying the different elements present in its structure.

What is a Helm Chart?

A Helm Chart in Kubernetes is a collection of files defining a set of Kubernetes resources. Helm Charts are Kubernetes YAML manifests combined into a single package. These manifest files help in a more seamless Kubernetes deployment and can be attached to the Kubernetes cluster.

Once packaged, installing a Helm Chart into the Kubernetes cluster is as easy as running a single helm install. It simplifies the deployment of containerized applications. Helm Charts help in defining, installing, and upgrading even the most complex Kubernetes application.

Describing a Helm Chart!

Helm has a certain structure for creating a chart. In order to create a new chart, run “helm create YOUR-CHART-NAME”. Once this is created, the directory structure looks like this,

Structure of a Helm Chart

After knowing what is a Helm chart, it’s time to know how to describe a helm chart. Here are the different parts you need to mention while creating a Helm Chart in Kubernetes. Let’s take a look at these elements of a Helm Chart.

Helmignore: This holds all the files that need to be ignored when packaging the chart. It is similar to .gitignore, in case of git.

Chart.yaml: This is where all the information related to the chart that is being packaged is put. So, for example, details such as the version number etc can be specified here. This is where all these details need to be specified.

Values.yaml: This is the file in which all the values that are to be injected into the templates are defined. Similar to terraform, Values.yaml is the same as helms variable.tf file.

Charts:This is where other charts on which the helm chart that is being structured depends on are stored. There might be a need to call another chart for letting the chart function properly.

Templates:This is the folder where the actual manifest that is being deployed with the chart is put. For instance,for deploying an nginx deployment that needs a service, configmap and secrets, there would be a deployment.yaml, service.yaml, config.yaml and secrets.yaml all in the template dir. They will all get their values from values.yaml from these.

The Conclusion!

This is how you can describe a Helm chart. Kubernetes deployment is a complex process that brings along its own challenges. Using Helm can help enterprises handle these complexities and ease the process of Kubernetes deployment.

Besides Helm, a platform such as BuildPiper for Kubernetes management can help. BuildPiper is an end-to-end Kubernetes & Microservices Application Delivery Platform that enables more than 10X reduced time & investments needed to onboard & securely manage the complete setup and deployment of Kubernetes & Microservices applications.

You may also enjoy reading:
[Challenges of Kubernetes & How to Solve it?]

To know more about its other interesting functionalities, schedule a demo today!

Read more about Helm, its benefits, what is a helm chart, the benefits of using a helm chart in Kubernetes deployment and the components of a helm chart, here in this article.

“Introduction To Helm, Helm Charts and its Components !”

The Benefits of using Helm!

Ruchita_Varma — Wed, 06 Jul 2022 12:53:31 +0000

Helm also known as the package manager for Kubernetes is a stalwart element within the Kubernetes ecosystem. It helps in application deployment by packaging all resources needed for a seamless Kubernetes deployment. Here, we talk about the benefits of using Helm. Let’s take a look!

A Kubernetes manifest defines the resources (e.g., Deployments, Services, Pods, etc.)that users want to create, and how they want these resources to run inside a Kubernetes cluster. This is why a manifest file is a must for Kubernetes Deployment.

Why use Helm?

Creating and maintaining Kubernetes YAML manifests for all the required Kubernetes objects can be time-consuming and complex. Helm simplifies this process and creates a single package that can be allocated to your Kubernetes cluster.

Benefits of using a Helm chart in Kubernetes!

Here’s more on what is a Helm chart used for. By making application deployment easy, standardized and hassle-free, Kubernetes Helm improves,
-Boosts productivity
-Reduces the complexity of deploying Microservices
-Enhances deployment speed

Boosts Productivity!

Using a Helm allows the software to deploy its test environments at the click of a button. For instance, in order to test a new feature, a developer would need a SQL database. There is no need for the development to go through the process of installing the software and then create all the databases & tables required. Instead, the teams can simply run a single Helm Install command to create and prepare the database ready for testing. This in turn saves the developers time and boosts their productivity.

Reduces Complexity!

Once the Helm chart is built, it can be used over and over again by anyone. By using the Helm chart in Kubernetes deployment, product teams can actually reduce complexities. The fact that developers can use the same chart for any environment reduces the intricacies of creating different charts for the dev, test and prod environment. The DevOps teams can simply tune in their Helm chart and make sure it is ready to be applied to any environment, be it in dev, test or prod. This way teams can leverage the benefits of using a production-ready chart in a dev environment.

Simplifies Deployments!

A helm chart makes it easy to set overridable defaults in the values.yaml file, allowing software vendors or administrators of charts to define a base set. Developers and users of Helm charts can override these settings when installing their charts as per their needs. If the default installation is required, then no override is required. This really simplifies the deployment process easing the developer’s tasks.

HELM really HELPS!

I’m pretty sure after reading this, you now have a clear understanding of what is a Helm chart used for. Deploying applications to Kubernetes is not a simple process as there are several other objects involved. This requires specific knowledge of all these components and what their functions are to successfully deploy those. Helm takes the complexity out of the process and makes Kubernetes deployment extremely simple and easy to handle.

Just like the helm enables a pilot to steer a ship, Helm enables a Kubernetes operator to have greater control of his/her Kubernetes cluster.

[Good Read:“3 Best Tools to Manage Your Kubernetes Cluster!”]

Other alternatives for managing a Kubernetes Cluster!

When it comes to deploying a Kubernetes cluster in a seamless manner, Helm charts can certainly help teams. A platform like BuildPiper can help. With BuildPiper, enterprises can empower their DevOps teams with an end-to-end Kubernetes & Microservices Application Delivery Platform that enables more than 10X reduced time & investments needed to onboard & securely manage the complete setup and deployment of Kubernetes & Microservices applications.

To know more about its other interesting functionalities, schedule a demo today!

Read more about Helm, its benefits, what is a helm chart, the benefits of using a helm chart in Kubernetes deployment and the components of a helm chart, here in this article.

“Introduction To Helm, Helm Charts and its Components !”