73 posts tagged with "engineering-metrics"

Jellyfish is good at what it was built for: portfolio-level visibility for VPs of Engineering at 200+ developer organizations. It surfaces "what percentage of engineering effort goes to growth vs. maintenance" in a board-deck-ready format. That's a real problem at real scale, and Jellyfish solves it.

The friction is the price tag and the fit. Public references and customer reports place Jellyfish contracts in the $50K-$250K/year range, with most deals near or above $100K. For a 60-engineer company that wanted "DORA + a bit of resource allocation", that's the wrong shape and the wrong invoice.

If you're searching "Jellyfish alternative" you're usually in one of two camps. Either you piloted Jellyfish and the price didn't survive procurement, or you're at 30-150 engineers and the platform is overbuilt for your actual question. Both are common. Here's the honest landscape in 2026.

Pluralsight Flow has had three names. It launched as GitPrime in 2015, was acquired by Pluralsight in 2019 and rebranded to Pluralsight Flow, then in 2024 was sold to Appfire as part of a broader divestiture. Customer experience tracked the rebrands: support response slowed, product roadmap stalled, and at least three of our customers reported their Flow renewal conversations went sideways in the post-Appfire transition.

If you're searching "Pluralsight Flow alternative" or still searching "GitPrime alternative" out of muscle memory, you're probably asking one of two questions. Either: is the platform still being meaningfully developed, or am I paying for legacy code? Or: my renewal is up and I want to evaluate the landscape honestly before signing again.

This piece answers both. We have a separate PanDev vs Pluralsight Flow head-to-head; this is the broader market view.

Sleuth shipped one of the cleanest DORA implementations on the market. Then in late 2024 it was acquired and folded into a larger DevOps suite, and by 2026 the standalone product feels less actively developed than the platforms around it. That's reason enough for many teams to shop around — not because Sleuth is bad, but because betting your delivery telemetry on a product that's no longer the parent company's headline matters.

This is not a hit-piece. Sleuth's deploy-correlation model still beats most competitors. But if you searched "Sleuth alternative" you already know the deal: you want options. Here are 5 — what each does well, what each gets wrong, and the honest pick for each shape of team.

Every engineering leader asks the same question: how much time do developers actually spend writing code?

Microsoft Research found that developers spend only 30-40% of their time writing code. A 2019 study by Haystack Analytics suggested closer to 2 hours. Our own IDE heartbeat data across B2B engineering teams confirms a median of 78 minutes per day.

Here's what the data actually shows and why it matters.

Forbes Kazakhstan dedicated pages 104–107 of their April 2026 issue to engineering intelligence — and to PanDev Metrics specifically. The article, titled "Доверься «большому брату»" ("Trust the Big Brother"), explored how data-driven development management is gaining traction across Central Asia and beyond.

Rather than republishing the piece, we want to highlight the parts that matter most: what our clients actually said, what the numbers show, and where the industry is heading.

Fred Brooks warned in The Mythical Man-Month (1975) that measuring programmer productivity by volume of code is a trap: adding more code isn't the same as adding more value. Fifty years later, some organizations still equate lines written with work done. The SPACE framework (Forsgren et al., 2021) explicitly cautions against single-dimensional activity metrics — yet the need they address is real: how do you measure whether your engineering team is delivering?

The answer isn't another vanity metric. It's a composite signal we call the Delivery Index.

"This should take two days." Three weeks later, the feature is still in progress.

Steve McConnell, in Software Estimation: Demystifying the Black Art, found that software projects typically overrun initial estimates by 28-85%. Brooks's Law from The Mythical Man-Month explains part of the reason: complexity grows non-linearly with scope, and adding people to a late project makes it later. The PM is frustrated. The developer feels guilty. The roadmap is fiction. And the entire organization has quietly accepted that engineering estimates are unreliable.

This isn't a people problem. It's a measurement problem. And it's fixable.

The Deloitte Global Outsourcing Survey consistently identifies "lack of visibility" as one of the top reasons outsourcing relationships fail. Your client pays for 160 hours per month per developer. But deep down, they wonder: were those really 160 hours of productive work? This single doubt has killed more outsourcing contracts than missed deadlines.

The problem isn't trust — it's the absence of proof.

The Deloitte Global Outsourcing Survey found that lack of transparency is the primary driver of client dissatisfaction in outsourcing relationships. Two companies pitch the same client. Same tech stack, similar rates, comparable portfolios. One says: "We deliver quality work on time." The other says: "Here's a live dashboard showing exactly what your developers are doing right now." Which one wins?

In 2026, the answer is obvious. Transparency isn't a nice-to-have — it's the differentiator.

Research on context switching shows that it takes an average of 23 minutes to fully regain focus after an interruption. Now multiply that by five projects, each with its own Slack channel, Jira board, and stakeholder expectations. You're an outsourcing PM managing five projects for five different clients. Each client thinks their project is your top priority. And every Monday morning, you spend the first two hours trying to remember where each project left off on Friday.

Sound familiar? This is the multi-project management problem — and it's the defining challenge of outsourcing project management.