Commits and pull requests tell you what was delivered. But they miss the hours of debugging, refactoring, and research that happen between pushes. IDE plugins capture that missing layer — how much time was spent coding, which files were touched, and when developers were most active.

PanDev Metrics offers plugins for VS Code, JetBrains (IntelliJ, PhpStorm, WebStorm), Eclipse, Xcode, Visual Studio, PL/SQL Developer, a Chrome extension, and a CLI for everything else. This guide covers installation and configuration for all of them.

Not every company can send engineering data to the cloud. Regulated industries, government contractors, and security-conscious organizations need their metrics platform on-premise — inside their own network, on their own servers. According to the CNCF Annual Survey, over 80% of organizations now run Kubernetes in production, making container-based on-premise deployment a well-understood operational pattern.

PanDev Metrics supports full on-premise deployment via Docker Compose (for small teams) and Kubernetes with Helm (for larger organizations). This guide covers both paths, including LDAP authentication, TLS certificates, and persistent storage.

Dashboards are great — until you need an answer that doesn't fit any pre-built chart. "What was our average PR review time last month, excluding the infra team?" That query doesn't have a button. It requires filtering, grouping, and calculating across multiple dimensions.

PanDev's AI assistant lets you ask questions like this in plain English. Powered by Google Gemini, it understands your engineering data and returns answers, charts, and tables in seconds. Gartner predicts that by 2026, over 80% of enterprises will have used generative AI APIs or deployed AI-augmented applications — natural-language analytics is part of that shift.

Your product team just shipped a new reporting dashboard. It took three sprints, involved four developers, a designer, and a QA engineer. How much did it actually cost?

If your answer is "I don't know" or "somewhere between $20K and $80K," you're not alone. Most engineering organizations cannot answer this question with any precision. According to Stripe's Developer Coefficient report, companies collectively spend over $300 billion annually on developer time — yet few can attribute those costs to individual features. That disconnect turns every product decision into a guess.

Every quarter, CTOs face the same uncomfortable meeting. The CEO asks: "We spent $2.4M on engineering last quarter. What did we get for it?" And the answer is usually a list of shipped features — not a financial return.

Engineering is the largest cost center in most technology companies, yet it's the one with the least financial accountability. Marketing can show customer acquisition cost. Sales can show revenue per rep. Engineering shows... velocity points? McKinsey's analysis of software developer productivity highlights this gap: engineering output is measurable, but most organizations haven't built the systems to do it.

It's time to change that.

Your engineering team has 40 developers across three offices, a mix of full-time employees and contractors, salary ranges from $60K to $190K, and contractor rates from $45/h to $150/h. Someone asks: "How much did Project X cost last month?"

You open a spreadsheet. You check Jira. You send three Slack messages. An hour later, you have a rough guess. With global IT spending projected to exceed $5 trillion in 2025, that level of imprecision is expensive at any scale.

A Series B SaaS company with a 35-person engineering team was spending nearly $800K per month on software delivery. The CEO wanted to cut costs. The board suggested reducing headcount. The CTO proposed a different approach: find the waste first, then eliminate it.

Six months later, monthly delivery cost dropped to roughly $540K — a reduction of more than 30% — while deployment frequency actually increased. No layoffs. No quality regression. McKinsey's research on developer productivity supports this pattern: the biggest efficiency gains come from eliminating process friction, not cutting headcount.

Here's the playbook.

It's budget season. The CTO submits an engineering budget request: $8.2M for next year, up 18% from this year. The CFO asks for justification. The CTO points to headcount growth, salary inflation, and a list of planned projects. The CFO pushes back: "Can we do it for $7M?" The CTO says no. They compromise at $7.5M.

Neither number is based on data. The CTO added a buffer to last year's spend. The CFO cut it by a round number. The compromise has no analytical basis. Both sides walk away slightly unhappy. A Deloitte CFO Survey found that technology spending is consistently one of the hardest budget categories for finance teams to evaluate — largely because the inputs are opaque.

This is how most IT budgets are built. It doesn't have to be.

WakaTime is one of the most well-known developer time tracking tools, with over 500K users, 40+ IDE plugins, and an annual "Yearly Wrapped" report that has become a community tradition. At $9/month for the Premium plan, it is one of the best values in developer tooling. PanDev Metrics is an Engineering Intelligence platform built for teams and organizations. They both track coding activity via IDE plugins — but that is where the similarity ends.

If you are evaluating both tools, this comparison will help you understand which one fits your needs.

LinearB is one of the more established players in the Engineering Intelligence space, known for strong DORA metrics implementation and workflow automation. PanDev Metrics is a newer platform that takes a broader approach — combining engineering metrics with financial analytics and on-premise deployment.

Both platforms aim to help engineering leaders make better decisions. But they differ significantly in pricing, deployment options, and the types of insights they provide. Here's a detailed, honest comparison.