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Cost per Accepted Change: The Metric That Matters When AI Writes Your Code

More commits, more pull requests, more deploys: switch on AI tooling and every counter goes up. None of them measures whether things got better. One number does: what it costs to get a single change through review and into production. Here is how to pull it from your Git and CI data.

DORA metrics tools: what each one can actually measure

Every tool in this market will show you four numbers. The question worth asking is which of them it measured, and which of them it was told.

DORA vs SPACE: which engineering metrics framework do you need?

One is a fixed set of four delivery outcomes. The other is a way of choosing what to measure at all. Teams treat them as competing options and then wonder why the numbers do not add up.

Iteration speed: what fast teams actually measure

The fastest iteration loops in the world right now are not in software. Understanding why they are fast says something uncomfortable about how most delivery teams work — and points at the handful of things worth measuring.

Pluralsight Flow is being retired. Here is what happens next.

Renewals closed on 30 June 2026 and the product retires at the end of 2027. Appfire is not recommending a replacement, so here is an honest look at the options — including when the answer is not us.

Cycle Time vs. Lead Time: Why the Difference Matters

Cycle time and lead time are often used interchangeably in Agile conversations, but they answer different questions — and mixing them up can create a lot of confusion.

Cycle time measures how long it takes for work to be completed once someone starts working on it. Lead time measures how long it takes from the moment work is requested until it reaches production or the customer. That difference sounds small, but it changes the story entirely.

Agile Data Blind Spots: What You're Not Seeing in Jira

Hidden Dependencies and Invisible Blockers

The Hidden Metrics Agile Teams Miss (And Why Velocity Alone Isn't Enough)

Your sprint dashboard shows 85% of story points completed. The burndown chart looks healthy. But features still miss deadlines. Tech debt grows. Your team is exhausted. What's wrong?
You have data everywhere — Jira is full of it, dashboards track everything, retrospectives are always scheduled. Yet somehow, you're drowning in visibility but starving for insight.


Flow Health: What Ticket Age Quietly Reveals About Your Delivery System

Most teams monitor throughput.

They know how many tickets were completed this sprint, how many story points moved across the board, and how many releases happened last month. Those numbers are easy to surface and easy to compare over time. The problem is that they often describe output without saying much about the condition of the system producing it.

5 Practical Steps to Deal With Slow Release Cycles

Most teams notice slow release cycles long before they can explain them. Features take longer to reach production than expected. Work sits in review queues for days. Releases become stressful enough that teams start avoiding them unless absolutely necessary. Eventually, delivery slows down to the point where planning becomes guesswork because nobody is confident about when work will actually ship.

AI Observability in Developer Workflows: What the Latest Research Actually Shows

AI has quietly settled into everyday development work. It shows up in code reviews, pull requests, documentation, and all the small decisions that keep things moving. What’s still missing, in many cases, is a clear understanding of what it’s actually doing there.
A recent paper, AI Observability for Developer Productivity Tools: Bridging Cost Awareness and Code Quality, takes a closer look at that gap.

Agile as a Platform: How It Slowly Gets Enshittified

Agile was introduced as a way to reduce friction, not create new layers of it. Teams adopted it because it helped them move faster, make decisions closer to the work, and respond to change without waiting for permission. For a while, that promise held up. Delivery improved, collaboration felt more natural, and processes stayed lightweight enough to adjust when needed.

Platform Engineering: Treating Your Platform Like a Product

For a long time, internal platforms were treated as infrastructure. Something you built once, maintained quietly, and expected teams to adapt to. If things worked, nobody noticed. If they didn’t, developers found workarounds.

That model doesn’t hold up anymore.

Embedded vs Platform vs Centralised SRE — Which Model Actually Scales?

 

As systems grow, reliability stops being something a few engineers can “keep an eye on” and turns into a structural concern. Incidents become harder to trace, dependencies less obvious, and small failures start to cascade in ways that weren’t visible before. At that point, the question is no longer how to improve reliability, but how to organise for it.

Measuring AgileEx: Transforming Team Experience into Actionable Insights for Agile Success

Agile transformations rarely fail because teams don’t follow ceremonies. They fail quietly, over time, when the experience of working within the system becomes frustrating, slow, or disconnected from outcomes. That experience — how teams plan, build, release, and improve — is what we call AgileEx (Agile Experience).

How to Align SLOs with User Experience — Beyond Uptime and Latency

Service Level Objectives are often presented as a way to bring clarity to reliability. In practice, many teams end up tracking what is easiest to measure rather than what is most meaningful. Uptime percentages and latency percentiles look precise on dashboards, yet they can give a false sense of confidence. A service can be “up” and still fail users in ways that matter—checkout flows that break halfway through, reports that arrive too late to be useful, or APIs that technically respond but return incomplete data.

5 Practical Steps to Improve Software Delivery (Without Adding More Process)

Software delivery rarely fails because teams don’t work hard enough. More often, the issue is a lack of clarity: where time is going, what is slowing things down, and which changes actually improve outcomes.

How to Set SLOs That Developers Actually Respect

Service Level Objectives (SLOs) have become a standard part of modern reliability engineering. They are supposed to help teams make informed decisions about reliability, prioritise work, and balance speed with stability.
       
Yet in many organisations, SLOs exist only on paper. They live in dashboards that nobody checks or in documentation that nobody remembers writing. Developers continue shipping features, operations teams continue firefighting incidents, and the SLOs quietly drift out of relevance.

SLOs for Internal Services — What to Track When You Don’t Have Users

Service Level Objectives (SLOs) are a cornerstone of modern reliability engineering. They help teams understand, measure, and maintain the reliability of the services they build. For public-facing services, this is usually straightforward: uptime, latency, error rates, or user satisfaction can all serve as meaningful indicators. But what happens when your service doesn’t have external users? Internal microservices, background jobs, data pipelines, and internal business systems still power your operations — but traditional user metrics don’t exist.

Features vs Non-Features Ratio: Understanding Your “Thinking Pies”

In software development, not all work is created equal. The ratio of features to non-features — the features/non-features ratio, or what we sometimes call the “thinking pies” — can be surprisingly telling about how your team is spending its cognitive and operational bandwidth.

SLOs in Cloud-Native & Distributed Architectures

As organisations scale, their software platforms become increasingly distributed. Services are no longer isolated — they communicate, depend on each other, and often operate across different teams, cloud regions, and technology stacks. While this architecture improves scalability and resilience, it also complicates reliability management.

SLO Dashboards That Tell a Story: What to Visualise — and What to Avoid

Most SLO dashboards answer a single question: “Did we meet the SLO?”
Unfortunately, that’s also the least useful question you can ask.
Great SLO dashboards don’t just report compliance. They tell a story — one that helps engineering, product, and leadership make better decisions.

When AI Doesn’t Help — Pitfalls, False Positives & How to Detect Them Early

n the previous articles in this series, we explored how to measure AI adoption, how to track output and quality, how AI affects developer experience, and how to combine those signals into a responsible AI impact dashboard. This article focuses on the less comfortable side of the story: what happens when AI doesn’t help — and how to detect that early, before damage accumulates.

Putting It All Together — How to Build an AI Impact Dashboard Without Breaking Trust or Teams

By now, most software organisations have accepted a simple truth:
AI is everywhere in development — whether leadership tracks it or not.
      
What’s still missing in 2025 is not tooling, but coherence.

DevEx vs. SPACE: How to Measure Developer Experience the Right Way

In the rapidly evolving world of software development, the old notion of “productivity = more code” is long dead. Modern engineering teams recognise that sustainable performance depends not just on output, but on the developer experience (DevEx) that underlies it.
      
Two influential frameworks have emerged to help teams think about this holistically: SPACE and DevEx. Each offers a structured way to capture what matters — but they serve slightly different purposes and deliver different insights.

Developer Experience & Long-Term Health: Measuring AI Adoption's Impact on Burnout and Skill Growth

AI tools don’t just change how code is written — they change how developers think, learn, and experience their work. And those effects rarely show up in PR metrics or dashboards until it’s too late.

This article focuses on Developer Experience (DevEx) and long-term team health — measuring whether AI adoption is sustainable over time, or quietly increasing burnout, cognitive load, and skill erosion beneath the surface.

Output Metrics — How to Accurately Track Code Throughput & Quality when Using AI

AI tools can help developers write code faster, suggest tests, and even automate parts of code review. But speed alone isn’t enough. Without measuring output quality, faster code could just mean more bugs, rework, or hidden technical debt. In this article, we explore practical techniques to track engineering output metrics, ensuring that AI actually improves productivity without compromising maintainability.

Measuring AI Adoption & Tool Usage — What to Track Before You Code

AI tools are increasingly embedded into developers’ daily workflows — from IDE autocomplete and chat-based assistants to AI-powered pull-request reviews and test generation. But before you try to measure whether AI improves productivity, quality, or Developer Experience, there’s a more basic question you must answer:
Are developers actually using AI — and how?

Can You Really Measure AI Impact on Developers? A Practical Framework

AI-assisted coding tools (like Copilot, AI pull-request reviewers, automated test generators, etc.) are becoming widely adopted — but the evidence for their impact on productivity and developer experience remains mixed. Some recent studies show improvements, others show no change or even slowdowns. 

Agile Astrology: When Your Burndown Chart Aligns With Mercury In Retrograde  

Agile is all about data… but sometimes, no matter how many dashboards we build, the team still behaves like their destiny is written in the stars. So today, let’s embrace a more cosmic approach to engineering analytics:
Agile Astrology — where your metrics reveal everyone’s secret zodiac sign. Is it scientific? Absolutely not.
Is it more accurate than your last sprint estimate? Almost definitely.

Psychological Safety Is an Engineering Metric — Here’s the Proof

Most Agile teams obsess over velocity, burndown charts, sprint goals, ceremonies, tooling, and frameworks. Yet a quiet story that recently surfaced on Reddit reveals something far more fundamental: “Agile doesn’t break when the process is wrong. It breaks when people feel like they can’t be honest.” In the post, a team looked perfect from the outside—standups were quick, the board was active, and everyone confidently nodded through planning. It seemed efficient.

When Continuous Delivery Isn’t Possible: How Teams Can Still Improve Developer Experience

Continuous delivery has become the holy grail in modern software development. The idea of shipping value to customers multiple times a day, collecting immediate feedback, and iterating rapidly is compelling. But for many software teams—particularly in hardware-heavy, regulated, or legacy-heavy domains—full continuous delivery (CD) is simply not feasible.

Killing the Daily Blocker: Data-Driven Ways to Free Your Developers

Every team has them — the daily blockers.
They show up in standups as “still waiting on access,” “tests are flaky again,” or “need someone to review my PR.”
Individually, each seems small. But collectively, they erode flow, focus, and morale.

The truth: most developer blockers aren’t random. They’re measurable, repeatable patterns — and that means they can be killed with data.

The Reality Behind AI for Developers: Prompting in Practice

Generative AI is no longer a novelty in development. Tools like Copilot, ChatGPT, and others are deeply embedded in many engineering workflows. But how exactly do developers use them, how reliable are they, and what patterns of prompting and conversation actually help produce useful code? That’s what this recently published paper by Daniel Otten, Trevor Stalnaker, Nathan Wintersgill, Oscar Chaparro & Denys Poshyvanyk set out to discover. 

AI + SonarCloud: From Static Analysis to Auto-Fixes

SonarCloud is great at detecting issues — code smells, bugs, vulnerabilities, and coverage gaps. But most teams treat it as a reporting tool, not an active participant in the delivery pipeline. The result? Issues pile up until a developer manually sifts through them.

By combining SonarCloud with AI-driven automation, we can go further: turning static analysis into auto-remediation workflows.

OpsEx + DevEx + AgileEx: The New Trinity of Delivery Success

Your software delivery quality depends on developer experience. A strong developer experience (DX) creates faster delivery cycles with fewer errors and happier developers. Companies across the industry have proven this repeatedly.

Meme-Driven Metrics: Why Humour Might Be the Ultimate DevEx Signal

When you think about Agile metrics, what comes to mind? Velocity, cycle time, deployment frequency, maybe even error budgets. But what if we told you that one of the most overlooked signals of Developer Experience (DevEx) isn’t in Jira, Git, or SonarCloud—it’s in memes.
      
Yes, memes. The Slack screenshot, the “This is fine” dog, the endless parade of SpongeBob reaction images—what your team laughs at might be just as important as what your team commits.

The Impact of AI in Programming: A New Era for Software Teams

Today, artificial intelligence is changing that equation. Far from being just a “co-pilot” for writing new lines of code, AI is increasingly becoming a maintenance partner, quality enforcer, and productivity amplifier. It promises not only to make individual developers faster but to reshape how software teams approach the lifecycle of code fundamentally.

Velocity in the Fall: How Seasonal Factors Affect Agile Metrics

When autumn arrives, it’s not just the leaves that change colour—your Agile metrics may shift, too. Teams often notice fluctuations in velocity, throughput, or cycle time during the fall season, and while it may look like a sudden drop in productivity, the reasons are often more human than technical. Understanding these seasonal dips and spikes helps leaders respond with context instead of overreaction.

Agile Pumpkin Spice: The Overhyped Practices You Can Safely Drop

Every fall, pumpkin spice creeps into everything: lattes, candles, cookies—even shampoo. It’s comforting, trendy, and a little overdone. Agile, too, has its own “pumpkin spice” — practices that sound great, look polished, and make teams feel like they’re being Agile, but don’t actually add much value.

Continuous Improvement Check-In: Your 9-Month Agile Health Report

By the time September arrives, your Agile team has completed three quarters of the year’s journey. It’s the perfect moment to pause, reflect, and make adjustments before the year-end sprint. This 9-month check-in offers a structured way to assess your Agile health, identify bottlenecks, and ensure your processes are primed for Q4 delivery.

Back-to-School for Teams: Relearning the Basics of Agile Execution

By September, many Agile teams have sprinted through countless standups, retros, and releases. But just like students who forget the fundamentals over summer break, even high-performing teams can develop bad habits or skip essential steps.

How the DORA Metrics Became the Standard for Measuring Software Team Performance

In recent years, if you’ve talked about measuring software delivery performance, you’ve probably heard of the DORA metrics—a set of four key indicators that help organisations understand how effectively their engineering teams deliver value. But where did these metrics come from? And why have they become the industry’s gold standard?

The Anatomy of Developer Panic: What Causes It and How to Prevent It

You’ve probably been there. A production system is down, a critical customer feature has stopped working, alerts are going off, and no one seems to know who’s in charge.
In that moment, logic gives way to instinct. Developers scramble, communication frays, and all anyone can think is: Fix it. Now.

Breaking Agile Rules: How Top Tech Companies Create Successful Hybrid Frameworks

Strict adherence to Agile methodologies might not always be the best approach. Top tech companies are breaking traditional rules to create more effective frameworks, which signals a revolution in hybrid project management.

DevOps Essentials vs. DevFluff: What’s Actually Helping Your Team (and What’s Just Vibes)

DevOps today is like a startup’s tech stack: overloaded, ever-evolving, and full of tools you’re not entirely sure anyone uses. Every week, something new is launched, promising to 10x your productivity or finally make your sprint retros meaningful.

The Truth About 99.999% SLO: Are You Being Misled?

Are you chasing ultra-high availability without knowing the cost? Learn why 99.999% SLOs often backfire—and how to set smarter, realistic reliability goals that truly support innovation.

Is DevOps a Culture, a Team, or Just a Fancy Word for Fixing What’s Broken?

Ask five engineers what DevOps is, and you'll get seven different answers. For some, it's a culture shift. For others, it's a team that handles tooling. And for many leaders, DevOps is a silver bullet they hope will solve delivery delays and on-call chaos.

Don't Let Summer Slow Your Sprints: Essential Agile Methodology Tips

Summer months bring a big problem to Agile methodology as productivity drops by up to 20%. Most families plan their vacations during this time - 56% of Europeans and 68% of Americans. Project deadlines don't pause because of sunny weather, and teams shouldn't choose between taking breaks and meeting targets.

What “Mean Time to WTF” Says About Your On-Call Experience

“It was 3 a.m. I opened the alert. Five dashboards, seven tabs, two Slack threads later — I still had no clue what was broken.”

If you’ve ever been on call and uttered “WTF?” within seconds of opening an incident alert, you’re not alone. In fact, we came up with a metric for that: Mean Time to WTF (MTTWTF).

AgileOps: Where Agile and SRE Meet

AgileOps is the convergence of Agile and SRE practices: a cultural and operational framework that blends iterative development with reliability-focused operations. This union helps organisations move fast without breaking things – and fix what does break, faster.

The Summer Slowdown: A Perfect Storm for DevOps Debt?

Summer hits the tech world differently.

Half the team is on vacation. Major releases are postponed. Deploys slow down. Slack goes quiet—except for the occasional “OOO until August 5th” message.

Cloud-Native ≠ Chaos: Using Metrics to Govern Decentralised Engineering

Cloud-native architecture has changed how enterprises work. About 80% of businesses now implement cloud-centric infrastructure at twice the speed compared to pre-pandemic times. 

How SREs Can Act as Internal DevEx Advocates

Developer Experience (DevEx) is no longer a soft metric — it’s a strategic advantage. But who in the organisation owns it? While product and platform teams often take the lead, there's an unsung hero uniquely positioned to champion meaningful DevEx improvements: the Site Reliability Engineer (SRE).

The Missing Backstage Plugin: DORA Metrics, Error Budgets, SLOs, and Sprint Flow in One View

Backstage.io Agile Analytics plugin: set up your developer portal for continuous improvement. Say goodbye to scattered dashboards and hello to real-time insights — right inside your developer portal. The Agile Analytics plugin for Backstage brings the power of engineering intelligence directly to your fingertips. 

Must-Read Books When Implementing DevOps

How The Phoenix Project and The Unicorn Project Inspire Real Transformation—and How Agile Analytics helps you realise this transformation.

Elastic Teams, Elastic Infrastructure: Making Sense of Cloud-Era Engineering

Cloud computing unlocked an era of elasticity. Infrastructure can scale up or down in seconds, adapt to usage patterns, and optimise cost dynamically. But here’s the catch: while infrastructure has evolved rapidly, the way we think about engineering teams hasn’t always kept up.

The 4 Key Metrics (4KM): Beyond the Buzzwords

1. Deployment Frequency: How often do you deploy to production?

DevEx vs. DevOps: What’s the Difference and Why Do Both Matter?

n the world of modern software development, two terms have gained a lot of traction: DevOps and DevEx (Developer Experience). While they may sound similar and are deeply connected, they serve very different purposes. Let’s break it down.

GDPR, NIS2 & DORA: Hidden Impacts on Your Software Pipeline

GDPR penalties can reach up to €20 million or 4% of global annual turnover. This regulatory framework represents just one piece of Europe's complex and ever-changing compliance requirements.

Why Top Software Teams Track Lead Time (And You Should Too)

Companies tracking lead time are 2X more likely to exceed their business goals. Lead time for changes, a key DORA metric, helps development teams worldwide measure their software delivery performance.


From Dev to Deploy: Visualising Developer Friction Points Using DevOps Metrics

Software development isn’t just about writing code – it’s about moving that code efficiently from idea to deployment. But too often, friction hides inside our DevOps pipelines, slowing teams down and frustrating developers. These bottlenecks rarely show up in a dashboard, and when they do, they’re hard to connect to real developer pain.

The solution? Use DevOps metrics to visualise friction points from Dev to Deploy – and take action before velocity and morale drop.

How to Track Agile Maturity Using Data: From Basics to Advanced

Only about 15% of organisations consider themselves fully mature in Agile.

The numbers paint an interesting picture. About 60% of organisations remain stuck in the second or third Agile maturity stages. This expresses a key challenge teams face as they try to evolve their Agile practices beyond simple implementation.

How to Break Into Site Reliability Engineering: Real-World Success Path

Software engineers solve operational problems differently through this innovative approach. SRE has become the industry-leading practice for service reliability, whatever the organization's size. The practice limits operational work to no more than 50% of an SRE's time, which keeps the focus on valuable engineering tasks. Ready to begin your SRE trip? Let's take a closer look!

Real-Life Examples of Service Level Objectives (SLOs)

Service Level Objectives (SLOs) aren’t just for massive cloud providers or SRE teams at Google. They’re highly relevant for any modern software development team that wants to improve reliability, performance, and customer experience, without burning out developers. In this article, we’ll examine real-world, actionable SLO examples used by actual engineering teams – from frontend to backend, APIs to CI/CD. 

The Hidden Flaws in Your Continuous Improvement Process (And How to Fix Them)

Continuous improvement is hailed as a cornerstone of Agile development, Lean manufacturing, and operational excellence. But let’s face it — not every continuous improvement (CI) process actually works.

Reducing Cognitive Load: The Missing Key to Faster Development Cycles

Developers spend over 10 times more time reading and understanding codethan writing it. This eye-opening ratio, noted by Robert Martin, shows why cutting down cognitive load is vital to speed up development cycles.

The Hidden Costs of Low Deployment Frequency in Modern DevOps

Elite DevOps teams deploy code 46 times more frequently than low performers, as revealed by the DORA Accelerate report. This stark difference highlights a crucial performance gap in today's digital world. Top teams deploy their code daily or weekly, while struggling teams manage only monthly or semi-annual deployments.

The Consulting SRE Model: Scaling Reliability Without Embedding Engineers

A small central SRE team that advises product teams on reliability instead of owning their systems. How the consulting SRE model works, when it fits, and where it fails.

How to Build a Continuous Improvement Process That Actually Works

Companies like Amazon and Apple have revolutionized their operations through continuous improvement. They've optimized everything from warehouse efficiency to product features. Our ground experience shows that efforts to improve products, services, and processes can deliver amazing results with proper execution. 

Embedded SRE Model: Elevating Reliability Through Direct Developer Support

In this article, we dive into the Embedded SRE model — a structure where reliability engineers work directly within development teams to foster a collaborative, hands-on approach to reliability and developer experience.

The Right Way to Do Backlog Refinement (and What to Avoid)

If you’ve ever found yourself thinking, “I sit through 90% of backlog refinement waiting for something relevant to me,” you’re not alone — but you’re also not doing refinement right.

Why Agile Compliance Is Failing (And How to Fix It)

Most regulated organizations fail to get results from Agile compliance, with a 75% failure rate. The evidence shows it works. Teams that use automated documentation tools cut their documentation time by 30% and stay compliant. Most organizations find it hard to balance Agile's speed and flexibility with strict regulatory requirements.

5 Must-Read Books to Improve Developer Experience (DevEx)

Improving Developer Experience (DevEx) is about far more than choosing the right tools. It’s about creating a culture and system where developers can focus, move fast, and enjoy their work. The best teams today recognize that great DevEx is essential for productivity, innovation, and retention.

Infrastructure SRE Team Model: When It Works Best

In a previous article on SRE models, we explored the Kitchen Sink SRE model — a common starting point for organisations launching their first reliability engineering efforts. Today, we're diving into another classic structure: the Infrastructure SRE team model.

The Anti-Pattern of Agile in Name Only (AINO): How to Spot It and Fix It

Over the last decade, Agile has become the de facto standard for software development. But with popularity comes dilution. Teams and organizations adopt Agile in form but not in spirit. Enter the anti-pattern: Agile In Name Only (AINO).


Building an Internal Developer Portal? Avoid These Common Mistakes

Gartner predicts that 75% of organizations with platform engineering teams will implement internal developer portals by 2026. Tech giants like Spotify, Netflix, and Lyft have already built their own internal developer portals. These companies are setting new standards in platform engineering.

Starting with SRE? Why the Kitchen Sink Model Might Be Your First Step

he Kitchen Sink SRE model serves as a starting point for organizations that start their reliability experience. This approach differs from specialized implementations. It creates a single SRE team with an unbounded scope that covers almost all services and workflows across the organization. 

The Intersection of Cloud and Agile: Boosting Development Productivity

Modern software development thrives at the intersection of cloud computing and agile methodologies. Organizations leveraging both experience faster development cycles, improved collaboration, and more reliable software delivery. But how exactly do cloud and agile work together to enhance developer productivity?

How SRE Practices Transform Developer Experience and Productivity

Modern developers spend less than two hours per day writing code. This surprising fact highlights why Site Reliability Engineering (SRE) is more than just system maintenance—it’s a critical enabler of developer productivity. 

The Science of Project Tracking: How Agile Analytics Improves Delivery Speed

Every project manager and agile team faces the same challenge: delivering work on time while maintaining quality. However, without effective project tracking, it’s easy to miss deadlines, exceed budgets, or fall into endless sprints with no real progress.

Understanding how to track project progress efficiently is crucial for improving agile delivery and avoiding project delays. 

The ROI of DevEx: Proving the Business Case for Developer Happiness

Organizations investing in developer experience see remarkable returns. ROI ranges from 151% to an impressive 433%. These numbers represent a radical alteration in how organizations value their development teams. The Developer Experience Index (DXI) draws from over four million measurement samples worldwide. 

Why Your SLOs Might Be Failing (And How to Fix Them)

Service Level Objectives (SLOs) are meant to keep your systems reliable, your customers happy, and your engineering team focused on what really matters. But what if your SLOs aren’t working?
Maybe your team is constantly firefighting incidents, or your error budgets run out too quickly. Maybe SLOs exist on paper, but nobody actually uses them to make decisions. If that sounds familiar, you’re not alone.

The Hidden Employee Retention Strategies That Actually Work in Agile Teams [2025 Guide]

51 million U.S. workers chose to leave their jobs in 2022. This massive talent exodus makes employee retention a vital priority today. Companies spend between $25,000 and $100,000 to replace just one employee who leaves. Traditional staff retention methods often miss the mark for agile teams that need to stay motivated. Our platform, Agile Analytics, helps teams work better together.

How to Connect DevEx Metrics with Business Success: Step-by-Step Guide

Most developers spend just 30% to 40% of their time writing code. Their typical 41-hour work week includes 4 hours to fix bad code and 17 hours to handle maintenance tasks. DevEx (Developer Experience) helps address these challenges. Companies that excel at DevEx consistently outperform their competition.

Understanding Employee Churn: Causes, Impact, and How Agile Analytics Can Reduce It

Learn what employee churn is, how to calculate it, and how Agile Analytics reduces turnover with data-driven insights.

Why Software Development Needs Better Collaboration, Not Just More Tools

For years, software teams have been flooded with tools—project management platforms, CI/CD pipelines, automated testing suites, and collaboration apps promising to make development smoother. And yet, despite this technological overload, teams still struggle with misalignment, inefficiencies, and bottlenecks.

Top Developer Experience Tools You Should Be Using in 2025

Developer Experience (DevEx) is more than just a buzzword—it’s a crucial factor in developer productivity, satisfaction, and retention. The right tools can eliminate friction, streamline workflows, and improve collaboration. In 2025, organizations are focusing on automation, feedback loops, and seamless integrations to enhance DevEx.

Why Data-Backed Decisions Are the Future of Business Software Development

If your business relies on software—whether it’s a customer-facing app, an internal tool, or an enterprise platform—you’re making software development decisions, whether you realize it or not. And if those decisions aren’t based on real data, you’re gambling with time, money, and your competitive edge.

Insights on DORA, SLOs, DevEx and AI

DORA metrics and flow

SLOs, error budgets and SRE

Developer experience

Measuring the impact of AI

All articles

Less guessing. More shipped software.