DEV Community: anhphan

SCRUM Team Role

anhphan — Sun, 08 Sep 2024 14:56:20 +0000

scrum

winglang

anhphan — Fri, 26 Apr 2024 02:51:38 +0000

Infrastructure and code in one language

A unified programming model that combines both infrastructure and application code into a single programming language.

Compiles to IaC (TF, CDK, etc.) & Javascript
Infrastructure resources are first-class citizens
Automatic IAM policies and other cloud mechanics

Local simulation

Stay in your creative flow with minimal context switching and immediate feedback
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Run your cloud application in your local environment
Visualize, interact, and debug locally
Write unit test for complete cloud architectures

Apply DevOps at the right level

Use any cloud service and compile to multiple cloud providers and provisioning engines, with full control over how your infrastructure is configured and deployed
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Cloud-agnostic SDK for maximum portability
Customizable infrastructure through plugins
Supports any provider in the Terraform ecosystem

Designed for humans

Easy to learn and interoperates with existing stacks and tools
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Syntax inspired by modern application development languages like TypeScript, JavaScript, Swift, and more
Statically-typed and simple language with powerful IDE tooling
Interoperates with npm modules, CDK constructs and Terraform providers

devops #winglang

Query DB SELECT * FROM
anhphan — Wed, 24 Apr 2024 08:02:52 +0000
SELECT * FROM

; Everyone knows it's been not good, but now I can read the whole bunch of consequences and it's interesting so I'll share it with you guys

Increased network traffic

Increased CPU usage on client side

Some query plan optimizations not possible

Server-side memory usage

Increased CPU usage on server side

Hard parsing/optimization takes more time

Cached cursors take more memory in shared pool - LOB Fetching #database.

Prometheus Server

anhphan — Tue, 23 Apr 2024 09:34:36 +0000

The Prometheus server is the core component responsible for scraping, storing, and querying metrics data.
The Prometheus server is designed for reliability and scalability, allowing it to handle large volumes of metrics data from numerous targets. Here’s a breakdown of its functionalities:

Data Scraping:

The Prometheus server regularly scrapes metrics data from configured targets.
It supports various protocols like HTTP, HTTPS, and SNMP for scraping metrics endpoints

Prometheus Configuration File:

The Prometheus configuration file is where you define the targets to scrape, the time intervals for scraping, and other configuration settings.
The Prometheus configuration file is written in YAML format and defines various aspects of Prometheus’ behavior.
Global Configuration:
The global configuration section contains settings that apply globally to Prometheus.
This includes parameters like the scrape interval, which determines how often Prometheus scrapes metrics from targets.
scrape_interval: Defines the interval at which Prometheus scrapes metrics data from targets.

evaluation_interval: Specifies the interval at which Prometheus evaluates alerting rules.

Scrape configuration defines the targets that Prometheus should scrape for metrics data.
Each scrape configuration specifies a job name and a list of targets to scrape. These targets could be specific endpoints or services job_name: Identifies a logical group of targets.

static_configs: Defines static targets to scrape, such as specific IP addresses and ports

Promethues- Architecture

anhphan — Mon, 22 Apr 2024 04:30:03 +0000

Prometheus gathers metrics from your applications and infrastructure. These metrics represent various aspects of your systems’ performance, such as CPU usage, memory consumption, request latency, and more. Prometheus collects these metrics over time, allowing you to understand trends, identify anomalies, and troubleshoot issues.
Key Components of Prometheus Architecture
Prometheus Server: The core component responsible for data collection, storage, querying, and alerting.
Time Series Database (TSDB): Stores time-series data efficiently, enabling fast querying and analysis of metrics.
Data Model: Defines how metrics are organized using metric names, labels, and values.
Exporters: These are tools that expose metrics from third-party systems as Prometheus metrics. Since Prometheus can only scrape metrics in its
Service Discovery: services are identified which are need to scraped.
Alert Manager: Handles alerts sent by the Prometheus server. It is responsible for deduplicating, grouping, and routing them to the correct receiver such as email, PagerDuty, or OpsGenie. It also takes care of silencing and inhibition of alerts.
Pushgateway: A middleware component that accepts metrics from jobs that cannot be scraped. This is typical for short-lived jobs or batch jobs that don’t expose an HTTP endpoint long enough for Prometheus to scrape. Metrics are pushed to the Pushgateway, and then Prometheus scrapes the Pushgateway to collect these metrics.
Targets: Any system or service that exposes metrics via an HTTP endpoint. This could be applications, infrastructure components, or external services.
Client Libraries: Libraries for instrumenting applications and services to expose their own metrics in a Prometheus-compatible format.
PromQL: The query language used to query and analyze metrics stored in Prometheus.
Visualization Tools: Various tools and dashboards can be used to visualize the metrics collected by Prometheus, such as Grafana.