Automated code review and profiling for development teams
AWS CodeGuru is an AWS service that provides automated code reviews and application profiling to find defects and optimize Java and Python applications; it's aimed at engineering teams and SREs who want continual code quality and performance insights with pay-as-you-go pricing based on analysis and profiling hours. Ideal for teams already on AWS, CodeGuru pairs static analysis (CodeGuru Reviewer) with runtime profiling (CodeGuru Profiler) under usage-based costs.
AWS CodeGuru is an Amazon Web Services offering that analyzes source code and application runtime to find bugs, security risks, and performance hotspots. The primary capability is split into CodeGuru Reviewer (static analysis for Java and Python pull requests) and CodeGuru Profiler (continuous runtime profiling for CPU/latency optimization). Its key differentiator is integration into AWS CI/CD pipelines and per-analysis/per-profile hour pricing that targets engineering and SRE teams. CodeGuru in the Code Assistants category is accessible via a free trial tier and pay-as-you-go pricing, making it practical for teams already using AWS.
AWS CodeGuru is a managed AWS service that launched as a public offering in 2020 to bring automated code review and runtime profiling into AWS developer workflows. Positioned as a DevOps and developer productivity tool, its core value proposition is to reduce defects and cut application costs by surfacing actionable recommendations: security and correctness findings from static analysis, and resource-usage hotspots from runtime profiling. CodeGuru is designed to integrate with AWS developer tools (CodeCommit, CodeBuild, CodePipeline) and common CI/CD workflows, so teams can get continual feedback during pull requests and in production-like environments.
CodeGuru Reviewer performs static analysis on pull requests and repository code to detect common coding defects, concurrency issues, resource leaks, and AWS API misuses. It supports Java and Python codebases and returns findings annotated directly in pull requests for CodeCommit, GitHub, and Bitbucket integrations. CodeGuru Profiler collects sampled runtime performance data, identifies CPU-bound or latency hotspots, correlates them with stack traces, and estimates potential cost savings by showing where code optimization would reduce compute costs.
The profiler runs continuously or on-demand and visualizes flame graphs and aggregated metrics in the AWS console. Both components provide prioritized recommendations with explanation, confidence levels, and links to remediation guidance. Pricing for AWS CodeGuru is usage-based and split across the Reviewer and Profiler features.
CodeGuru Reviewer charges per 100,000 lines of code analyzed for repository analysis and per-code-review request costs for pull request scanning; specific prices vary by region and are published on the AWS pricing page. CodeGuru Profiler bills per profiling hour (sampled agent runtime hours) with a lower cost for continuous profiling compared to on-demand heavy sampling; AWS also provides a 90-day free trial for new Profiler customers in some regions and occasional free-tier allowances for initial evaluations. There is no flat monthly "Pro" subscription; teams estimate costs by projected analysis runs and profiler hours.
Enterprise customers with large-scale usage may negotiate custom enterprise pricing through AWS support or their account team. Development teams, SREs, and DevSecOps engineers commonly use CodeGuru for pre-merge code quality checks and production performance tuning. For example, a Senior Backend Engineer uses CodeGuru Reviewer to reduce code-review time by surfacing likely bugs in Java pull requests, while an SRE uses CodeGuru Profiler to reduce EC2/ECS CPU usage and estimate cost savings from optimizations.
It's best-suited to organizations already on AWS who want tight integration with AWS developer services. Compared to generic static-analysis tools, CodeGuru's integrated runtime profiling and AWS billing/cost estimate hints differentiate it, though teams seeking language breadth beyond Java/Python may consider alternatives like SonarQube or GitHub Advanced Security for different trade-offs.
Three capabilities that set AWS CodeGuru apart from its nearest competitors.
Which tier and workflow actually fits depends on how you work. Here's the specific recommendation by role.
AWS CodeGuru is useful when one person needs faster output without adding a complex workflow.
AWS CodeGuru should be tested for collaboration, quality control, permissions and repeatable results.
AWS CodeGuru is worth buying only if the pilot shows measurable time savings or quality gains.
Current tiers and what you get at each price point. Verified against the vendor's pricing page.
| Plan | Price | What you get | Best for |
|---|---|---|---|
| Free trial / Free tier | Free | Limited trial profiling hours or reviewer scan credits in some regions | Small evaluation projects and proofs-of-concept |
| CodeGuru Reviewer (pay-as-you-go) | Exact regional price per 100,000 lines (see AWS) | Billed per 100K lines analyzed and per pull-request scan; region-dependent | Teams needing pull-request static analysis on demand |
| CodeGuru Profiler (pay-as-you-go) | Exact regional price per profiling hour (see AWS) | Billed per profiling hour per instance; continuous profiling supported | SREs optimizing runtime costs and latency |
| Enterprise / Negotiated | Custom | Custom quotas and SLAs via AWS account team | Large orgs with high-volume analysis needs |
Scenario: A small team uses AWS CodeGuru on one repeated workflow for a month.
AWS CodeGuru: Free | Freemium | Paid | Enterprise ·
Manual equivalent: Manual review and execution time varies by team ·
You save: Potential savings depend on adoption and review time
Caveat: ROI depends on adoption, usage limits, plan cost, output quality and whether the workflow repeats often.
The numbers that matter — context limits, quotas, and what the tool actually supports.
What you actually get — a representative prompt and response.
Choose AWS CodeGuru over GitHub Advanced Security if you prioritize AWS-native profiling and cost-estimation tied to runtime performance.
Real pain points users report — and how to work around each.