Automated SLO Management

Collaborate across your teams to define SLOs and Error Budgets aligned to user happiness and business goals. Delight your customers by deploying code faster with better reliability.

Dashboard displaying service status with Checkout marked as healthy at 100% error budget remaining and Catalog Service Uptime needing attention at 35% error budget remaining.Dashboard showing SLO status with 'Checkout' healthy at 100% error budget remaining and 'Catalog' in observe status with 35% error budget remaining.
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3D grid of white hexagons forming waves over a dark background.Digital blue hexagonal grid forming a wave-like surface on a dark background.

SLO configuration in minutes

Define SLOs, SLIs and track Error Budget burn rates for all your services across multiple observability data sources. Increase transparency across your organization by collaborating with your development, deployment and reliability teams in a single place.

Dashboard showing metric graph for valid requests with performance over time, and a control panel for setting thresholds, selecting 'Verification' metric, and defining SLI value greater than 0.35.Dashboard showing a metric for valid requests with a line graph and a threshold-based configuration selecting 'Verification' metric and setting SLI value to be greater than 0.35.

Next-generation CI/CD For Dummies

Stop struggling with tools—master modern CI/CD and turn deployment headaches into smooth, automated workflows.

Timeline graph showing deployment, infrastructure change, incidents, feature flag change, and chaos events between 9:35 PM and 10:25 PM with a lowest health score of 79 and 16 anomalies.Graph showing system health score timeline with events including deployment, infrastructure change, incidents, feature flag change, and chaos events between 3 PM and 10:25 PM, highlighting a lowest health score of 79 at 9:35 PM to 10:25 PM.

Change Impact Analysis

Resolve issues faster by understanding the impact of every change related to your deployments, infrastructure, feature flags, chaos experiments, incidents and more on the SLO performance and health of your service.

Automated Governance

Use reliability guardrails in your pipeline templates, along with your SLO data to determine if deployments should proceed. Allow your best developers continue to deliver highly reliable software at high velocity while putting guardrails in place for other developers or sensitive projects.

Flowchart showing a process with steps: Start Test, Test Plan, Policy Set with 2 policies, a status check, Deployment with 2 deployments, and Stop. Below, a policy evaluation error indicates pipeline execution stopped due to policy failures related to ErrorBudgetPolicy with error budget under 70%.
Screenshot of a policy set evaluation error indicating the pipeline execution could not proceed due to policy evaluation failures, specifically an error budget remaining for Users service in the prod environment being less than 70%, marked as failed.

Configure observability integrations and more

Harness applies AI and ML to observability data to determine if software is reliable.

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Management today

Deploy faster with better reliability

Service Reliability Management