Agile Metrics
Dashboard.

Stop wasting time building unnecessary tests and accelerate your sprints.

Request a Live Demo

Agile Metrics
Dashboard.

Stop wasting time building unnecessary tests and accelerate your sprints.

Request a Live Demo

What are Agile Metrics?

Agile development teams and their management use agile metrics to measure the development process, estimate productivity, determine the quality and predictability of the software they are developing, and assess the strength of their team. Rather than measuring “what” or “how much” their team is achieving, agile teams use metrics to measure the value they deliver to customers.

Agile methodologies place a special emphasis on quality because the end goal is to deliver working software to users. Quality is also manifested in internal aspects that are not directly visible to customers, such as code quality, maintainability, and technical debt

What are Agile Metrics?

Agile development teams and their management use agile metrics to measure the development process, estimate productivity, determine the quality and predictability of the software they are developing, and assess the strength of their team. Rather than measuring “what” or “how much” their team is achieving, agile teams use metrics to measure the value they deliver to customers.

Agile methodologies place a special emphasis on quality because the end goal is to deliver working software to users. Quality is also manifested in internal aspects that are not directly visible to customers, such as code quality, maintainability, and technical debt

Challenges with Software Metrics
in Development Organizations
.

Not Enough
Information

Modern development teams don’t have the data they need to answer questions such as: How successful were our bug fixes or tests? What is the quality of our tests? And, have these tests improved, if so by how much? Because teams do not have this level of visibility, there is usually no way to plan for maintenance in future sprints.

Software Metrics are Difficult
to Standardize

It is common to see different metrics, or the same metrics with different meanings, used across development organizations. Agile methodologies encourage this by allowing teams to pick their own definition of story points, and their own Definition of Done. Non-standard metrics make it difficult for management to compare the performance of their teams, departments, and projects, and to see how they are changing over time.

Software Metrics Can Drive Non-Productive Behavior

Developers tend to adjust their work habits according to their performance metrics. If an organization encourages and rewards an increase in LOC, developers will try to write a lot of code, even if it isn’t tight or efficient. If an organization encourages and rewards code coverage, developers will put a lot of effort into unit tests at the expense of other test types, which may be more important.

Challenges with Software Metrics
in Development Organizations
.

Software
is Intangible

Software is inherently difficult to measure. Treating the code as a “work product” that must be analyzed leads to a very narrow assessment of software, which usually does not reflect the value delivered to the customer.

Software Metrics are Difficult to Standardize

It is common to see different metrics, or the same metrics with different meanings, used across development organizations. Agile methodologies encourage this by allowing teams to pick their own definition of story points, and their own Definition of Done. Non-standard metrics make it difficult for management to compare the performance of their teams, departments, and projects, and to see how they are changing over time.

Software Metrics Can Drive Non-Productive Behavior

Developers tend to adjust their work habits according to their performance metrics. If an organization encourages and rewards an increase in LOC, developers will try to write a lot of code, even if it isn’t tight or efficient. If an organization encourages and rewards code coverage, developers will put a lot of effort into unit tests at the expense of other test types, which may be more important.

The Sealights Platform

An Agile Metrics Dashboard

SeaLights is a Quality Intelligence Platform that provides the necessary data and intelligence to compute new, meaningful metrics like Investment in Testing and Production Readiness. SeaLights combines data about code changes, production uses and test execution, to provide:

Test Gap Analysis

Identifyies areas where code was recently changed or executed in production but was not tested. Test gaps are the best place to invest R&D and QA resources to improve quality.

Test Impact Analysis

SeaLights Smart Test Execution Engine cuts the testing cycle time by 50% to 90%. It identifies and executes the minimum subset of tests required without compromising quality.

Release Quality Analytics

SeaLights performs real-time analytics on hundreds of thousands of test executions, code changes, builds and production events to assess the readiness of a release. These analytics show which build is best and let you know which build provides the highest quality for your users.

A Quality Intelligence Platform provides actionable insights that can steer teams and software organizations in the right direction.

Learn more

The Sealights Platform

An Agile Metrics Dashboard

SeaLights is a Quality Intelligence Platform that provides the necessary data and intelligence to compute new, meaningful metrics like Investment in Testing and Production Readiness.

SeaLights combines data about code changes, production uses and test execution, to provide:

Test Gap Analysis

Identifyies areas where code was recently changed or executed in production but was not tested. Test gaps are the best place to invest R&D and QA resources to improve quality.

Test Impact Analysis

SeaLights Smart Test Execution Engine cuts the testing cycle time by 50% to 90%. It identifies and executes the minimum subset of tests required without compromising quality.

Release Quality Analytics

SeaLights performs real-time analytics on hundreds of thousands of test executions, code changes, builds and production events to assess the readiness of a release. These analytics show which build is best and let you know which build provides the highest quality for your users.

A Quality Intelligence Platform provides actionable insights that can steer teams and software organizations in the right direction.

Learn more

How Software Quality Intelligence
Can Provide Visibility

As a result of the limitations of today’s software metrics, development organizations don’t have the metrics they need to effectively evaluate and manage software development projects, due to:

Missing data.

There is no central repository of data showing quality risks in applications and tests across all testing levels.

High complexity.

Complex software projects have thousands of tests, millions of lines of code that are in constant flux, and a large number of build artifacts. Calculating risk or holistic test coverage, even if the data was readily available, is infeasible.

Learn more

How Software Quality Intelligence
Can Provide Visibility

As a result of the limitations of today’s software metrics, development organizations don’t have the metrics they need to effectively evaluate and manage software development projects, due to:

Missing data..

There is no central repository of data showing quality risks in applications and tests across all testing levels.

High complexity.

Complex software projects have thousands of tests, millions of lines of code that are in constant flux, and a large number of build artifacts. Calculating risk or holistic test coverage, even if the data was readily available, is infeasible.

Learn more

Monitoring Tests & Test Frameworks.

The SeaLights metrics dashboard collects data about the tests that were run for each software version, and their results. Including unit, functional, UI, integration, end-to-end, and manual tests.

Tracking Code
Changes.

Code changes are risky. It’s important to correlate tests with recently changed code and production usage, to identify high priority features for testing. SeaLights can monitor and identify untested code changes in a specific build, across a period of time, and can compare two or more builds

Tracking Code Usage
in Production..

The SeaLights metrics dashboard provides visibility into which tests represent wasted effort and are not necessary, and which parts of the software are at risk of quality issues. Sealights applies business criticality weights to different code areas. They provide a visualization of the features that are in active use and the features that are effectively “dead code”.

Monitoring Tests & Test Frameworks.

The SeaLights metrics dashboard collects data about the tests that were run for each software version, and their results. Including unit, functional, UI, integration, end-to-end, and manual tests.

Tracking Code
Changes.

Code changes are risky. It’s important to correlate tests with recently changed code and production usage, to identify high priority features for testing. SeaLights can monitor and identify untested code changes in a specific build, across a period of time, and can compare two or more builds

Tracking Code Usage
in Production..

The SeaLights metrics dashboard provides visibility into which tests represent wasted effort and are not necessary, and which parts of the software are at risk of quality issues. Sealights applies business criticality weights to different code areas. They provide a visualization of the features that are in active use and the features that are effectively “dead code”.

Learn More About Agile Metrics, Read our White Paper

Regression Testing in the Microservices Age

Most applications based on a microservices architecture have between dozens to hundreds of services. This means that organizations moving from a monolithic to a microservices infrastructure go from one build and one test pipeline (however large) to hundreds of builds and multiple test pipelines.

In this white paper, we explain how testing in a microservices environment is dramatically different than in a monolithic application.

These differences create five major challenges for teams maintaining high-velocity microservices apps:



  • High complexity with low visibility



  • Complex and unpredictable rollback of changes



  • Limited visibility across the organization for changes made to individual components



  • Very long run time for full regression across all microservices



  • Decreasing marginal benefit of new tests

We will show how Quality Intelligence Platforms can mitigate these challenges, create visibility and avoid slowing down development with unplanned, ineffective, or slow running tests.

By submitting this form I agree that SeaLights may process my data in the manner described in SeaLights Privacy Policy.

Learn More About Agile Metrics, Read our White Paper

Regression Testing in the Microservices Age

Most applications based on a microservices architecture have between dozens to hundreds of services. This means that organizations moving from a monolithic to a microservices infrastructure go from one build and one test pipeline (however large) to hundreds of builds and multiple test pipelines.

In this white paper, we explain how testing in a microservices environment is dramatically different than in a monolithic application.

These differences create five major challenges for teams maintaining high-velocity microservices apps:



  • High complexity with low visibility



  • Complex and unpredictable rollback of changes



  • Limited visibility across the organization for changes made to individual components



  • Very long run time for full regression across all microservices



  • Decreasing marginal benefit of new tests

We will show how Quality Intelligence Platforms can mitigate these challenges, create visibility and avoid slowing down development with unplanned, ineffective, or slow running tests.

By submitting this form I agree that SeaLights may process my data in the manner described in SeaLights Privacy Policy.