{"id":18697,"date":"2026-06-25T17:07:26","date_gmt":"2026-06-25T17:07:26","guid":{"rendered":"https:\/\/testgrid.io\/blog\/?p=18697"},"modified":"2026-06-25T17:07:29","modified_gmt":"2026-06-25T17:07:29","slug":"flaky-tests","status":"publish","type":"post","link":"https:\/\/testgrid.io\/blog\/flaky-tests\/","title":{"rendered":"Flaky Tests in CI\/CD: Causes, Fixes, and Prevention"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">You run a test, detect a failure, analyze the issue, and then find out that the same test passed in the next execution under the same conditions. This is especially frustrating in large CI\/CD test suites.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">You might be wasting time fixing failures that aren\u2019t caused by real defects, which directly impacts team productivity and slows release cycles.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">If you\u2019re experiencing high test flakiness in automated pipelines, this blog will help you address the issue. We\u2019ll cover causes of flaky tests, reliable detection methods, and management strategies.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Improve test stability, reduce maintenance effort, and accelerate CI\/CD releases with TestGrid. <a href=\"https:\/\/public.testgrid.io\/signup?form=cotester-starter-package\">Request a free trial today<\/a>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<section class=\"wp-block-custom-tldr-summary tldr-block\"><p class=\"tldr-label\">TL;DR<\/p><ul class=\"tldr-list\"><li><span>A flaky test is an automated test that intermittently passes or fails under identical conditions without code changes.<\/span><\/li><li><span>Common causes include timing issues, unstable environments or networks, fragile scripts, and shared test data.<\/span><\/li><li><span>Flaky tests slow CI\/CD pipelines, disrupt smoke\/regression suites, increase maintenance, and delay releases.<\/span><\/li><li><span>You can detect them by running repeated executions, analyzing logs\/results, and using automated monitoring tools. <\/span><\/li><li><span>Best practices include configuring retries, managing test data effectively, and designing deterministic tests.<\/span><\/li><\/ul><\/section>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>What Is a Flaky Test?<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Flaky tests are automated tests that pass in one run and fail in another without any changes to the app code, the test code, or the test configuration. These tests can result from unstable <a href=\"https:\/\/testgrid.io\/blog\/test-environment\/\">test environments<\/a> or external dependencies.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Flaky tests can behave unpredictably and produce non-deterministic results across executions, which is why they\u2019re hard to reproduce and diagnose. This can reduce the overall reliability of your automated test suites and software quality.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>How Do Flaky Tests Affect Your QA Workflows?<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:18px\"><strong>1. Lower confidence in automation reports<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">When your test failures don\u2019t consistently indicate actual defects, your QA team can\u2019t fully trust the test results. They have to spend additional time investigating whether the failures happened because there\u2019s an issue in the code or from an unstable <a href=\"https:\/\/testgrid.io\/blog\/how-to-write-test-cases\/\" data-type=\"link\" data-id=\"https:\/\/testgrid.io\/blog\/how-to-write-test-cases\/\">test case<\/a>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:18px\"><strong>2. Slower CI\/CD pipelines and delay in releases<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Flaky tests can slow down your CI\/CD pipelines by causing builds to fail unexpectedly. Your app code could be functioning correctly, but false negatives caused by flaky tests can force your teams to rerun tests, examine failures, and validate results before they can even proceed with deployments. These extra verification steps increase your execution time.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:18px\"><strong>3. Negative impact on regression and smoke tests<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Smoke and <a href=\"https:\/\/testgrid.io\/blog\/regression-testing\/\">regression tests<\/a> help you quickly check the functionality of your app after you make code changes or before releases. If your test suites have flaky tests, they may create false alarms and make your team believe a new build is faulty even if it\u2019s not. Unreliable regression and <a href=\"https:\/\/testgrid.io\/blog\/smoke-testing-everything-you-need-to-know\/\">smoke test<\/a> results can block your release pipelines.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:18px\"><strong>4. Higher maintenance<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Fixing flaky tests requires frequent updates, refactoring, and monitoring. You may have to adjust update locators, improve <a href=\"https:\/\/testgrid.io\/blog\/test-data-management-guide-techniques\/\">test data management<\/a>, or address environment issues to keep your tests stable. This can take up a significant portion of your time and move your focus away from core QA tasks.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Common Causes of Flaky Tests<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">There\u2019s no one single cause of flaky tests. There could be issues within your test framework, scripts, frameworks, or the supporting&nbsp;<a href=\"https:\/\/testgrid.io\/blog\/what-is-test-infrastructure\/\">test infrastructure<\/a>. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">These are some of the most common reasons that can create test flakiness:<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><tbody><tr><td><strong>Cause<\/strong><\/td><td><strong>Description<\/strong><\/td><\/tr><tr><td><em>Sync issues and race conditions<\/em><\/td><td>If a test interacts with an element before an async wait condition is met or dynamic content fully loads, it may pass or fail inconsistently across your executions<\/td><\/tr><tr><td><em>Unstable network or environment<\/em><\/td><td>Variations in your test environment, such as network latency, available system resources, browser configurations, or performance degradation caused by memory leaks, can cause tests to behave differently across execution conditions<\/td><\/tr><tr><td><em>External dependencies and third-party services<\/em><\/td><td>Tests that rely on APIs, databases, payment gateways, authentication providers, or other external services can become flaky if those dependencies experience delays, outages, rate limits, or unexpected response changes<\/td><\/tr><tr><td><em>Fragile test scripts and unstable locators<\/em><\/td><td>Dynamic attributes, complex XPath expressions, or frequently changing UI elements can cause your scripts to break<\/td><\/tr><tr><td><em>Reused or shared test data<\/em><\/td><td>When multiple tests share the same data, records, or user accounts, the changes made by one test can affect another, leading to inconsistent behavior and test order dependency, particularly when tests run in parallel or across multiple environments<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Also Read<\/strong>: <a href=\"https:\/\/testgrid.io\/blog\/why-your-test-suite-is-high-maintenance\/\">Why Your Test Suite Is High Maintenance<\/a><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Effective Strategies to Detect Flaky Tests<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">You now know what flaky tests are. The next step is to learn the methods that can help you spot them.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:18px\"><strong>1. Run repeated test executions<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Run the same test repeatedly under the same conditions and compare the results.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Say, for example, when you execute a login test 20 times under the same test environment, credentials, and app build, it should ideally pass all 20 runs. But if it passes 17 times and fails 3 times without any code changes, it indicates that the test may be flaky.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">You can implement automated reruns in your CI\/CD pipeline to speed up the process and troubleshoot non-deterministic tests faster.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Learn More<\/strong>: <a href=\"https:\/\/testgrid.io\/blog\/test-automation\/\">Guide to Software Test Automation: Frameworks, Tools, and Best Practices<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:18px\"><strong>2. Analyze logs, screenshots, and recordings<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">You should assess execution logs, screenshots, and session recordings from both your failed and successful runs. The comparison between these <a href=\"https:\/\/testgrid.io\/blog\/test-artifacts\/\">test artifacts<\/a> will help you detect app behavior, timing, test data, or environment conditions that are causing the intermittent failures.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Look for inconsistent error messages that show up only in certain executions<\/li>\n\n\n\n<li>Compare execution timestamps to spot delays, timeouts, or slow-loading components<\/li>\n\n\n\n<li>Check if the elements were unavailable, hidden, or not fully loaded when interactions happened<\/li>\n\n\n\n<li>Review the screenshots for unexpected pop-ups, overlays, or notifications<\/li>\n\n\n\n<li>Compare your browser, device, network, and environment configs across passing and failing runs<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:18px\"><strong>3. Use automated flaky test detection tools<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A <a href=\"https:\/\/hs-145518994.f.hubspotemail-eu1.net\/hubfs\/145518994\/bitrise-mobile-insights-2025-report.pdf\" target=\"_blank\" rel=\"noopener\">Bitrise report<\/a> shows that dev teams who invest in monitoring tools encounter <em>25% fewer flaky reruns and higher build success rates<\/em>. When your test suites grow, manually identifying flaky tests can get tough. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">These tools can help you simplify the process:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/testgrid.io\/blog\/test-management-tools\/\">Test management and reporting tools<\/a> allow you to assess historical test results and spot tests with inconsistent execution outcomes<\/li>\n\n\n\n<li>Browser automation frameworks like Playwright can help you collect traces, screenshots, videos, and execution logs for identifying false failures<\/li>\n\n\n\n<li>Connecting with <a href=\"https:\/\/testgrid.io\/blog\/ci-cd-tools\/\">CI\/CD tools<\/a> such as Jenkins, GitHub Actions, and GitLab CI enables you to configure automated test reruns and compare results across multiple executions<\/li>\n\n\n\n<li>Test observability platforms like Datadog CI Visibility let you track your flaky test rates, execution trends, and recurring failure patterns<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Managing Flaky Tests in CI\/CD<\/strong><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>1. Replace static waits with explicit waits<\/strong><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Static waits pause your execution for a fixed duration regardless of whether the required condition is met, which can make your tests sensitive to network latency, server load, and CI environment performance.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">You should rather apply explicit waits, which stop execution only until a specific element state, API response, or app condition is satisfied, and improve test reliability.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Learn More<\/strong>: <a href=\"https:\/\/testgrid.io\/blog\/test-environment-management\/\">Test Environment Management: Key Challenges and Solutions<\/a><\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>2. Isolate tests and remove shared state<\/strong><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Since shared databases, user accounts, files, or environment settings can create unintended dependencies that cause test failures, you must design tests that can execute independently without relying on data, configurations, or artifacts created by other tests.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">For that, you can create dedicated test data, reset app state between executions, and ensure each test performs its own setup and cleanup.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>3. Apply shift-left testing for early detection<\/strong><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Run your tests during local development, pre-merge checks, and pull requests. This will help you find synchronization issues and unstable assertions before they reach your CI environments. This also allows you to easily trace failures back to recent code changes and reduce the time spent on root cause analysis and troubleshooting.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Also Read:<\/strong> <a href=\"https:\/\/testgrid.io\/blog\/what-is-shift-left-testing\/\">Shift-Left Testing: Definition, Benefits, Challenges, and Best Practices<\/a><\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>4. Improve locator strategies for stability<\/strong><\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Stable and unique locators are generally more reliable than dynamic IDs, element positions, or complex XPath expressions, which can become invalid after layout updates.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Therefore, use dedicated test attributes, stable IDs, or accessibility attributes, and review locators regularly to ensure they remain resilient as your app changes.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Flaky Test Examples Across Frameworks<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Flaky tests can happen in any <a href=\"https:\/\/testgrid.io\/blog\/test-automation-framework\/\">automation framework<\/a>. But the underlying causes might vary depending on how the framework handles browser interactions, synchronization, network requests, and test execution.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><tbody><tr><td><strong>Test framework<\/strong><\/td><td><strong>Examples&nbsp;<\/strong><\/td><\/tr><tr><td><em>Flaky Selenium tests<\/em><\/td><td>&#8211; Interacting with an element before it becomes visible or clickable, resulting in intermittent <strong>ElementNotInteractableException <\/strong>errors<br><br>&#8211; Browser-specific failures where a test passes in Chrome but behaves differently in Firefox or Safari due to rendering and timing differences<br><br>&#8211; Tests failing with <strong>StaleElementReferenceException<\/strong> when a page refresh or a DOM update invalidates a previously located element<\/td><\/tr><tr><td><em>Flaky Cypress tests<\/em><\/td><td>&#8211; Assertions failing because app state has not finished updating after an asynchronous API call or background process<br><br>&#8211; Tests which depend on arbitrary<strong> cy.wait()<\/strong> delays become unstable when execution speeds vary between local and CI environments<br><br>&#8211; Interactions failing when elements are re-rendered by frameworks such as React or Vue during test execution, causing Cypress to lose its reference to the original element<\/td><\/tr><tr><td><em>Flaky Playwright tests<\/em><\/td><td>&#8211; Tests attempting to interact with elements immediately after navigation when additional client-side rendering is still in progress<br><br>&#8211; Tests can become unstable when concurrency increases through multiple browser contexts, pages, or parallel executions that share state or depend on the same test resources<br><br>&#8211; Failures occur when network requests, API responses, or dynamic content take longer than expected and exceed configured timeouts<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Best Practices to Reduce Flaky Tests in Test Automation<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:18px\"><strong>1. Configure automatic test retries<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Automatic retries help you identify intermittent failures that are caused by transient issues such as temporary network disruptions, infrastructure glitches, or short-lived service unavailability. Make sure you track retry occurrences to distinguish real <a href=\"https:\/\/testgrid.io\/blog\/defect-report\/\">defects<\/a> from unstable test behavior.<\/p>\n\n\n\n<figure class=\"wp-block-table is-style-stripes\"><table class=\"has-fixed-layout\"><tbody><tr><td><strong>Pro tip<\/strong><br>Don\u2019t assess your test stability based only on final pass rates. You should monitor metrics like retry frequency and retry success rates, and look for increasing retry counts, as this can indicate your tests are unstable and relying on reruns to pass.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:18px\"><strong>2. Maintain clean test data<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">You need to implement processes which help you keep your test data accurate, consistent, and aligned with your current app state. Outdated, corrupted, or unrealistic datasets can generate misleading test outcomes and make it hard for you to diagnose and reproduce failures.<\/p>\n\n\n\n<figure class=\"wp-block-table is-style-stripes\"><table class=\"has-fixed-layout\"><tbody><tr><td><strong>Pro tip<\/strong><br>Check your test data regularly, remove obsolete records, and ensure that your datasets reflect real-world usage scenarios. You can also version-control your test data to track data changes and quickly identify if a failure is related to a recent data modification.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:18px\"><strong>3. Make test stability a shared quality goal<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Flaky tests can occur because of changes in app behavior, infrastructure, test frameworks, or deployment environments. And these factors are not controlled by a single team. That\u2019s why you need to make test stability a shared responsibility among your development, QA, and DevOps teams.<\/p>\n\n\n\n<figure class=\"wp-block-table is-style-stripes\"><table class=\"has-fixed-layout\"><tbody><tr><td><strong>Pro tip<\/strong><br>Establish clear ownership for investing and resolving flaky tests. Define stability metrics (e.g., flaky test rate, false failure rate, quarantine test count) and track them in periodic quality reviews.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-size:18px\"><strong>4. Design tests for determinism<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Tests that depend on the current system time or specific execution timings can become unstable if dates, time zones, processing speeds, or response times vary across your test environments. This is why you must <a href=\"https:\/\/testgrid.io\/blog\/test-case-design-techniques\/\">design tests<\/a> with predictable inputs and controlled dependencies.<\/p>\n\n\n\n<figure class=\"wp-block-table is-style-stripes\"><table class=\"has-fixed-layout\"><tbody><tr><td><strong>Pro tip<\/strong><br>You can reduce the sources of unpredictability by mocking random number generators, fixing timestamps, and using consistent test configurations. This will make it easy for you to reproduce test outcomes and resolve flaky tests.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Using TestGrid to Reduce Flaky Tests and Improve Reliability<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">For your team to efficiently detect flaky tests, they need stable automation, better visibility into test executions, and reliable test-monitoring mechanisms to track test stability.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/testgrid.io\/\">TestGrid<\/a> is a unified, AI-powered testing platform that lets you automate your web and mobile tests faster with low-code, no-code, and record-and-playback capabilities.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The platform\u2019s AutoHeal technology repairs your broken tests by identifying new locators and objects. This helps you prevent unnecessary test failures and reduce the maintenance effort.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">TestGrid provides detailed execution insights, logs, screenshots, and reporting capabilities so your team can analyze failures more efficiently and detect recurring flakiness patterns.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Moreover, the platform offers support to automation frameworks like Selenium, Appium, and Cypress. This enables you to build and manage deterministic test suites in your chosen framework and scale execution across CI\/CD pipelines.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Build resilient testing workflows with AI automation, intelligent reporting, and enterprise-grade execution capabilities using TestGrid. <a href=\"https:\/\/public.testgrid.io\/signup?form=cotester-starter-package\">Request a trial<\/a> today.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Frequently Asked Questions (FAQs)<\/strong><\/h2>\n\n\n<div id=\"rank-math-faq\" class=\"rank-math-block\">\n<div class=\"rank-math-list \">\n<div id=\"faq-question-1782389843189\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \">What\u2019s the difference between flaky and failing tests?<\/h3>\n<div class=\"rank-math-answer \">\n\n<p>A failing test consistently reports a defect or unmet requirement. A flaky test alternates between passing and failing under the same conditions, making it unreliable.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1782389883230\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \">How do flaky tests affect CI\/CD pipelines?<\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Flaky tests slow pipelines by forcing teams to rerun suites, validate results, and separate real defects from false failures, which delays releases.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1782389905706\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \">Which flaky tests should be fixed first?<\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Prioritize high-impact tests, those failing most often, blocking deployments, affecting critical business functions, or appearing in smoke\/regression suites.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1782389933039\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \">How many flaky tests are normal in a suite?<\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Healthy suites may have 1\u20132% flaky tests. Aim for near zero. Above 5% signals systemic or environmental issues that need immediate attention.<\/p>\n\n<\/div>\n<\/div>\n<\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>You run a test, detect a failure, analyze the issue, and then find out that the same test passed in the next execution under the same conditions. This is especially frustrating in large CI\/CD test suites. You might be wasting time fixing failures that aren\u2019t caused by real defects, which directly impacts team productivity and [&hellip;]<\/p>\n","protected":false},"author":13,"featured_media":18708,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[209],"tags":[],"class_list":["post-18697","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-test-automation"],"acf":[],"images":{"medium":"https:\/\/testgrid.io\/blog\/wp-content\/uploads\/2026\/06\/flaky-tests-300x169.webp","large":"https:\/\/testgrid.io\/blog\/wp-content\/uploads\/2026\/06\/flaky-tests-1024x576.webp"},"_links":{"self":[{"href":"https:\/\/testgrid.io\/blog\/wp-json\/wp\/v2\/posts\/18697","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/testgrid.io\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/testgrid.io\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/testgrid.io\/blog\/wp-json\/wp\/v2\/users\/13"}],"replies":[{"embeddable":true,"href":"https:\/\/testgrid.io\/blog\/wp-json\/wp\/v2\/comments?post=18697"}],"version-history":[{"count":6,"href":"https:\/\/testgrid.io\/blog\/wp-json\/wp\/v2\/posts\/18697\/revisions"}],"predecessor-version":[{"id":18709,"href":"https:\/\/testgrid.io\/blog\/wp-json\/wp\/v2\/posts\/18697\/revisions\/18709"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/testgrid.io\/blog\/wp-json\/wp\/v2\/media\/18708"}],"wp:attachment":[{"href":"https:\/\/testgrid.io\/blog\/wp-json\/wp\/v2\/media?parent=18697"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/testgrid.io\/blog\/wp-json\/wp\/v2\/categories?post=18697"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/testgrid.io\/blog\/wp-json\/wp\/v2\/tags?post=18697"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}