Stop Guessing Why Teams Are Slow
You know some teams ship fast and others are blocked. But you don't have the data to know why. CloudShip gives you real-time visibility into deployment velocity, lead time, incident patterns, and bottlenecks—so you can unblock teams and accelerate delivery.
You Have Velocity Metrics But No Actionable Insights
Jira shows story points. GitHub shows commits. DataDog shows incidents. But nobody connects them. So you know Team A ships twice as fast as Team B—but you don't know if it's because of architecture, process, incidents, or dependencies. You're managing teams blind.
Questions You Can't Answer Today
"Why is Team B's deployment velocity half of Team A's?"
Is it architecture complexity? Incident load? Cross-team dependencies? You're guessing.
"Which teams are bottlenecked by incidents?"
DataDog shows incidents. Jira shows velocity drops. Nobody correlates them.
"Is our CI/CD pipeline the bottleneck?"
GitHub shows build times. But are slow builds actually slowing down deployments?
"Are we improving or slowing down over time?"
Need lead time trends, deployment frequency trends. Data exists but isn't tracked.
Jira shows story points. GitHub shows commits. DataDog shows incidents. But nobody connects them. So you know Team A ships twice as fast as Team B—but you don't know if it's because of architecture, process, incidents, or dependencies. You're managing teams blind.
Leadership asks why engineering is slowing down. You pull Jira reports, GitHub stats, incident logs. Three days later, you have disconnected metrics that don't explain root causes. Still can't answer: "What's actually blocking our teams?"
You're managing engineering teams with vanity metrics instead of actionable operational intelligence. You need connected data, not disconnected dashboards.
Blocked Teams, Slow Delivery, Missed Targets
Without operational visibility, you can't unblock teams. That team struggling with velocity? They're spending 40% of their time on incident response. You didn't know because incidents and velocity aren't connected. That team hitting targets? Their lead time is increasing—early warning you missed.
What This Costs Teams:
The Incident-Blocked Team
Velocity tanked. You blamed process. Turns out 50% of their time was firefighting incidents from legacy architecture. Took 2 months to discover.
The Slowly Degrading Pipeline
Teams complain deploys are slow. But by how much? From 10 min to 45 min over 3 months. You didn't see the trend until productivity tanked.
The Hidden Dependency Hell
Team velocity dropped 30%. Retrospective blamed "unclear requirements." Real cause: waiting on 3 other teams for API changes. Data didn't show it.
Without operational visibility, you can't unblock teams. That team struggling with velocity? They're spending 40% of their time on incident response. You didn't know because incidents and velocity aren't connected. That team hitting targets? Their lead time is increasing—early warning you missed.
Your high-performing engineering orgs have operational intelligence. They see bottlenecks in real-time. They correlate velocity drops with incident spikes, slow builds, or cross-team dependencies. They unblock teams before delivery slips. You're finding out after the sprint is lost.
Every sprint without operational visibility is another sprint delivering less than your team's potential. You need real-time insights, not post-mortem dashboards.
Connected Engineering Intelligence: Velocity + Incidents + Dependencies
CloudShip correlates GitHub (commits, deploys, PRs), Jira (velocity, cycle time), DataDog (incidents, performance), and CI/CD pipelines—automatically. See which teams are blocked and why. Unblock them with data, not guesses.
How You Manage Teams Today:
- → Look at Jira velocity reports (story points completed)
- → Ask teams in standups why they're slow
- → Check GitHub commit counts (vanity metric)
- → Teams say "lots of fires" or "waiting on dependencies"
- → Can't quantify it, can't prioritize fixes
- → Management asks for improvement plans without data
With CloudShip Engineering Intelligence:
- → See deployment frequency + lead time per team
- → Correlate velocity drops with incident spikes automatically
- → Track CI/CD build time trends (catch degradation early)
- → Identify cross-team dependency bottlenecks
- → Unblock teams with specific, data-driven actions
- → Show leadership measurable improvements over time
CloudShip correlates GitHub (commits, deploys, PRs), Jira (velocity, cycle time), DataDog (incidents, performance), and CI/CD pipelines—automatically. See which teams are blocked and why. Unblock them with data, not guesses.
Team-Level Operational Metrics
Deployment frequency, lead time, change failure rate, MTTR—per team. See who's shipping fast and who's blocked.
Automatic Root Cause Correlation
Velocity drop? CloudShip shows if it's incident load, slow builds, or cross-team dependencies. No more guessing.
Trend Detection
Catch velocity degradation early. See build times increasing before teams start complaining. Fix problems before they hurt delivery.
Unblock Teams With Data, Not Retrospectives
These are the questions you ask every week—now with connected operational data:
"Why is Team B's velocity half of Team A's?"
See incident time per team, build/deploy duration, cross-team wait times. Root cause is in the data, not team surveys.
Velocity + Incidents + Pipeline metrics, correlated
"Are we getting faster or slower?"
Track lead time, deployment frequency, change failure rate over quarters. Show leadership measurable improvement (or catch degradation early).
DORA metrics tracked over time
"Which teams are spending too much time on incidents?"
Correlate incident frequency with velocity per team. See which teams are firefighting vs. shipping features.
Incident impact on delivery metrics
"Is our CI/CD pipeline slowing teams down?"
Track build/test/deploy times over weeks. Catch 10-min builds becoming 45-min builds before teams revolt.
Pipeline performance trends
"Which architectural changes improved velocity?"
Before/after metrics on lead time and deployment frequency. Prove that microservices migration or monolith split actually helped.
Architecture impact on delivery
"Do we need to hire more engineers or fix process?"
See if bottleneck is capacity (all teams maxed) or process (one team blocked by incidents/dependencies). Data drives decisions.
Resource allocation intelligence
This is engineering intelligence for high-performing teams. Not vanity metrics. Operational data that shows you how to unblock delivery.
Your CISO Won't Block This
Other engineering intelligence tools require uploading GitHub access, CI/CD credentials, and production metrics to vendor clouds. CloudShip is different: agents run in your infrastructure. GitHub tokens, CI/CD access, monitoring data—all stay internal. Only aggregated metrics flow to the Platform.
Why this matters to engineering leadership:
You get operational intelligence without security blocking it. Engineering deploys agents locally. Your CISO approves because credentials stay internal. You get your team velocity dashboards immediately, not after months of vendor security reviews.
Stop Managing Teams Blind
Get connected engineering intelligence: velocity, incidents, dependencies, pipelines—all correlated. Unblock teams with data, not guesses.