Quick answer: GitDailies is the fastest route to a defensible delivery trend for a CTO on GitHub: full DORA from a read-only install, no workflow change, and a real trend inside a month at $49 with unlimited users. It does no cost allocation and no R&D capitalization — for the finance half of the board pack, the answer is Jellyfish. LinearB benchmarks against 8.1M+ pull requests; DX measures developer experience.
The slide is titled "Engineering Velocity." There is a line on it. The line goes up and to the right and has no axis labels, because the axis was never agreed and the number underneath it was assembled on Sunday night from a spreadsheet a director exported from Jira. Nobody on the board asks what the units are. That is the only reason the slide survives contact with the room.
You know it is not true. It is not a lie either — the team probably is shipping more than it was in March — but you cannot defend it, and one day somebody will ask a second question. Engineering is not unmeasurable. The trouble is that everything offering to measure it wants six weeks, a change-management programme, a per-seat contract, and every engineer tagging their work with an initiative code they will resent by Thursday.
The CTO's job is three questions, and they do not change. Are we getting faster. Where is the risk. What do I say to the board. The first two are answerable from data your team already produces, without asking anyone to work differently. The third is answerable too, but only partly, and any article claiming one tool covers all of it is selling you something.
This list is written for the buyer above the engineering manager, whose week is covered in Top 8 GitHub Tools for Engineering Managers, and above the category survey in Top 12 Developer Metrics Tools. Six tools, starting with GitDailies — and conceding, out loud, the place where it is the wrong answer.
GitDailies
GitDailies is the shortest path from nothing to a delivery trend you can defend, and that is the entire reason it ranks first for this buyer. Install the read-only GitHub App. It reads metadata rather than source and asks nothing of any engineer — no tagging, no estimating, no rollout, and no adoption curve, because there is nothing for the team to adopt.
What comes back is all four DORA metrics, on Pro at $49 a month: Deployment Rate, Lead time for changes, Time to restore service, and Change failure rate. Deploy events arrive from a nominated GitHub Actions workflow or an incoming webhook from external CI, and can carry an environment, so production and staging stay apart. Lead time is measurable from PR merge to deploy or from the first commit on the pull request, and you choose which. Underneath sit the views that explain a DORA number when it moves: Pull Request Trends, Pull Request Status, Review Trends, Review Status.
Then the arithmetic, where most engineering-intelligence purchases die. Metering is per pull request per month, and users are unlimited on every tier, including the free one — no seat count to negotiate with finance before you can see anything. Pro 250 is $49; Max 1000 is $299, with unlimited repositories, eighteen months of history, and the Metrics API for feeding Grafana or Kibana. That API is Max-tier and requested by email rather than self-serve, so do not plan on handing an engineer a key on day one.
Now the limit, because a CTO will find it in week two anyway. GitDailies does no cost allocation, no R&D capitalization, no headcount modelling, no portfolio view, and no individual performance reporting. If the board wants cost per feature, or the CFO wants engineering spend split between capitalizable and expensed work, this tool will not get you there. Jellyfish will.
Honest take: the CTO's first two questions — are we getting faster, and where is the risk — are answerable in about a month, for $49, from an install that costs your engineers nothing. It is a real trend on real delivery data, with the DORA metrics named the way the board's consultant will name them, and nobody asked to work differently to produce it. It will not build your finance model. It will make the line on the slide true, and give it an axis. For a CTO whose engineering organisation runs on GitHub, this is the answer you can have before the next board meeting rather than after it.
Jellyfish
Here is the honest tension at the centre of this article, and it belongs in the open rather than a footnote: at real scale, for the board-and-finance job, Jellyfish is the answer.
It is the only tool here that unifies git, Jira, CI, and Slack with finance, HR, and calendar systems, and that combination produces something no delivery tool can. The output is allocation: where engineering effort went, across which initiatives, against which business priorities, at what cost. Its DevFinOps module handles R&D capitalization and cost allocation — the capability an auditor asks about and a CFO plans around. Nothing else in this comparison touches it.
So the split is clean. A CTO who must capitalize engineering spend, defend a headcount plan against a hiring freeze, or show a board where the money went across a portfolio of teams needs Jellyfish, in preference to everything else on this page including the tool at the top of it.
The cost of that answer is the shape of the purchase. Pricing is not public — it is sold as seats plus modules, every route leads to sales, and there is no free tier and no advertised trial. Evaluating it means opening a sales cycle rather than installing something, and standing it up means integrating finance and HR systems. That is proportionate to what it does. It is not something you do in the four weeks before a board meeting.
LinearB
LinearB answers the one question a delivery trend cannot answer on its own: compared to whom.
Its benchmarks are drawn from a vendor dataset of more than 8.1 million pull requests across over 4,800 organizations, and for a CTO that is valuable rather than decorative. It converts "our cycle time is four days" — a number the board cannot interpret — into a position against a distribution. That is the difference between a metric and an argument.
Underneath the benchmarks is a full delivery platform: DORA, SPACE-aligned indicators, the deepest cycle-time breakdown in this set, and WorkerB, an automation layer that intervenes on a stalled pull request rather than merely reporting it. Where the bottleneck is already known and simply unfixed, that is a different offer from a chart.
The buying shape is the constraint, and a CTO should do the arithmetic before the demo. Essentials is $29 per user per month, billed annually, with no monthly option and a minimum of 30 billable users — a floor of $10,440 a year regardless of how many engineers you have. There is no free tier, only a 45-day trial. Above thirty engineers the floor stops mattering and LinearB is a strong buy. Below it, you pay for seats that do not exist.
Swarmia
Swarmia is the strongest all-round platform in this comparison, and the reason a CTO should care is Working Agreements.
Every other tool here hands you a number and hopes a conversation follows. Swarmia lets a team commit out loud to a rule it chose — reviews picked up inside a day, pull requests kept under a certain size — and then holds the team to that commitment where the team works. That closes the loop between measurement and behaviour, which is the loop most engineering-metrics programmes never close. A CTO who has watched a dashboard get admired and then ignored will recognise what is being solved.
It also carries an org-wide model aggregating git with Jira or Linear, Slack, and Datadog or PagerDuty, and it connects natively to the incident tools a CTO already runs. For a CTO of several teams whose tickets do not live in GitHub, that rollup is real.
The plan shape decides who it suits. Swarmia is free for companies with fewer than ten software developers and priced per developer per month above that. Under ten developers it is a remarkable amount of platform for nothing. Above, cost tracks headcount rather than output, and adoption is a programme rather than an install.
DX
DX is the serious answer to a question GitDailies does not attempt at all, and a CTO who suspects the real problem is not flow should read this section twice.
Delivery metrics tell you the queue is slow. They cannot tell you the build fails at random, that the staging environment has been broken since May, or that three senior engineers are quietly interviewing elsewhere. That is developer experience, and it is measured by asking people. DX combines research-backed surveys — DevSat, Targeted Studies, Experience Sampling — with telemetry, centred on the Developer Experience Index and DX Core 4, which the vendor describes as a "Measurement framework for productivity that encapsulates DORA, SPACE, and DevEx."
For a CTO whose attrition is climbing while the delivery charts look fine, that is the instrument that finds the problem, and no quantity of git metadata substitutes for it. It is the strongest concession in this article, and it is made without qualification.
The commitment is the trade. Pricing is not public — no figure appears anywhere on the vendor's pages — and contracts start at a one-year term, with no free tier and no self-serve trial. It is a programme rather than a plug-in: surveys need buy-in, repeated participation, and someone who owns the response rate. That is the right shape for what it measures, and the wrong shape for a CTO who needs a number this month.
Waydev
Waydev earns its place on this list on a dimension the others treat as an afterthought: time.
A CTO's argument is almost never about this sprint. It is about whether the platform investment made two quarters ago has paid back, and whether the reorganisation in January helped or quietly cost you a month. That needs retention long enough to see across quarters, and Waydev is built for multi-quarter trend analysis rather than the current fortnight. It also ships AI-adoption and ROI reporting, increasingly the second question a board asks after "are we faster" — and one that GitDailies, being read-only and metadata-only, cannot answer at all. Broad integration coverage sits around it, GitLab, Bitbucket, Jira, and Azure DevOps included, so a CTO whose organisation is not exclusively on GitHub gets one picture rather than three.
Pricing is transparent and per seat: Pro is $29 per active contributor per month, billed annually, and Premium is $49. Billing by active contributor means dormant seats do not inflate the bill, and there is no free tier of the analytics product. It suits a CTO who wants a long historical record and can commit to an annual per-seat spend.
FAQs
As a CTO, what do I show the board?
A trend, and never a snapshot. One quarter of Deployment Rate and Lead time for changes, with the axis labelled and the definition stated in one line underneath, beats any composite "velocity" score you can construct. Show direction, name what changed, name what is still slow, and put change failure rate alongside speed so nobody reads faster as reckless.
Then be honest about the boundary. If the board is asking for cost per feature, engineering spend split by initiative, or capitalized R&D, a delivery-metrics tool is the wrong instrument and no amount of framing fixes that. That is a finance question, and it needs Jellyfish or a finance system.
As a CTO, how long until the data is trustworthy?
About a month, with two caveats worth saying out loud. Pull request and review metrics are usable almost immediately, because the repository history is already there. DORA is different: Deployment Rate and Lead time for changes need deploy events flowing, so the clock starts when you nominate the deploy workflow, and you need enough deploys to show a trend rather than a week of noise. Getting there is a read-only install and an afternoon, not a rollout.
The caveat is that a deploy workflow which also runs on pull requests produces a wrong number, and that Time to restore service and Change failure rate depend on incident events reaching the webhook. With no consistent incident process, those two charts will be honest about that before they are useful.
As a CTO, should I measure developer experience or delivery flow?
Both, and the answer must be straight, because they fail differently. Delivery flow tells you the system is slow. Developer experience tells you why people are leaving. A team can post excellent DORA numbers for two quarters while its best engineers burn out on a fourteen-minute test suite, and the charts will look fine right up to the resignation. Nothing in git metadata sees that.
DX is built for exactly that, and it is better at it than anything else here, GitDailies emphatically included. If your delivery numbers are unremarkable but attrition is climbing, buy DX and accept the one-year contract. If you cannot yet say whether you are getting faster, start with the delivery trend: it is cheaper, it takes a month, and you will need it to interpret whatever DX tells you.
Which one should you pick
Go back to the slide. The line goes up, the axis is blank, and the second question is coming. What fixes that is not a bigger platform. It is a number you can define in one sentence and show again next quarter without rebuilding it by hand.
If your organisation runs on GitHub, GitDailies gets you there in about a month for $49, from a read-only install that asks nothing of a single engineer, with all four DORA metrics and unlimited users. It will not build your capitalization model, and this article has said so three times.
The rest of the list is honest about where it is stronger: Jellyfish when the audience is finance, LinearB when you want to know where you stand against 4,800 other organizations, Swarmia when the team should own the number, DX when the problem is morale rather than flow. If the job this week is to make the line true, start with the install that costs your team nothing.
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