Etcd Releases Download NEW!

etcd is a strongly consistent, distributed key-value store thatprovides a reliable way to store data that needs to be accessed by adistributed system or cluster of machines. It gracefully handles leaderelections during network partitions and can tolerate machine failure, evenin the leader node.Learn more

etcd versions are expressed as x.y.z, where x is the major version, y is the minor version, and z is the patch version, following Semantic Versioning terminology.New minor versions may add additional features to the API.

Etcd Releases Download

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The etcd project maintains release branches for the current version and previous release. For example, when v3.5 is the current version, v3.4 is supported. When v3.6 is released, v3.4 goes out of support.

When we launched etcd 3.4 back in August 2019, our focus was onstorage backend improvements, non-voting member and pre-vote features. Since then,etcd has become more widely used for various mission critical clustering and databaseapplications and as a result, its feature set has grown more broad and complex. Thus,improving its stability and reliability has been top priority in recentdevelopment.

Today, we are releasing etcd 3.5. The past two yearsallowed for extensive iterations in fixing numerous bugs, identifyingoptimization opportunities at scale, and evolving its surrounding ecosystem.The etcd project also became aCNCF graduated projectduring this time frame. This release is the result of continuous evolution andgrungy, thankless tasks done by the etcd community.

In this blog post, we review the most notable changes to etcd 3.5, and present aproject road map for future releases. For a complete list of changes, seeCHANGELOG 3.5. For more updates, follow us on Twitter @etcdio. To getetcd, see Install.

Given that etcd often handles sensitive data, improving and maintaining securityposture is our highest priority. In order to have a comprehensive understandingof etcd security landscape, we completed third-party security audits: The firstreport was published in February 2020, where we identified (and fixed) variousedge cases and high severity issues. For more information, see security auditreport.

The migration to structured logging is complete. etcd now defaults tozap logger that has a reflection-free,zero-allocation JSON encoder. We have deprecatedcapnslog that logged withreflection-based serialization.

Each etcd cluster maintains its own cluster version, a value agreed on by thequorum of the cluster. Previously, downgrading such cluster versions (e.g., etcdminor version from 3.5 to 3.4) was not supported in order to protect againstincompatible changes.

etcd reliability and correctness are of utmost importance. That is why webackport all critical bug fixes to previous etcd releases. The following arethe notable bugs we identified and fixed during etcd 3.5 development:

Kubernetes, the most prominent user of etcd, queries the entire keyspace to listand watch its cluster resources. This range query happens whenever the resourceis not found in the kube-apiserver reflector cache (e.g., requested etcd revisionhas been compacted, see kube-apiserver v1.21code),often causing slowness in reads from overloaded etcd servers (see GitHubissue). In such cases,kube-apiserver tracing warns as below:

Figure 1: etcd heap usage during a slow request warn logging for computing response size of a protocol buffer message. 61% of the heap was allocated in the proto.Size call path that encodes all key-value pairs in the message to compute the size.

The etcd 3.4 release made backend read transactions fully concurrent by copyingtransaction buffers rather than sharing between writes and concurrent reads (seecode change from 3.4 release).However, such a buffering mechanism comes with unavoidable copy overhead andnegatively impacted write-heavy transaction performance, as creating concurrentread transactions acquires a mutex lock which then blocks incoming writetransactions.

If a transaction includes a PUT (update) operation, the transaction instead shares the transaction buffer between reads and writes (same behavior as 3.3) in order to avoid copying buffers. This transaction mode can be disabled via etcd --experimental-txn-mode-write-with-shared-buffer=false.

Figure 3: etcd transaction ratio with a high write ratio. The value at the top is the ratio of reads and writes. The first ratio, 0.125, is 1 read per 8 writes. The second ratio, 0.25, is 1 read for 4 writes. The value at the right bar represents the inverse ratio of transaction throughput before and after etcd/pull/12896. With the shared buffer approach for writes, the transaction throughput is increased up to 2.7 times.

Figure 4: etcd transaction ratio with a high read ratio. The value at the top is the ratio of reads and writes. The first ratio, 4.0, is 4 reads per 1 write. The second ratio, 8.0, is 8 reads per 1 write. The value at the right bar represents the inverse ratio of transaction throughput before and after etcd/pull/12896. With the shared buffer approach for writes, the transaction throughput is increased up to 25%.

Figure 5: etcd transaction ratio with a high write ratio. The value at the top is the ratio of reads and writes. The first ratio, 0.125, is 1 read per 8 writes. The second ratio, 0.25, is 1 read per 4 writes. The value at the right bar represents the inverse ratio of transaction throughput before and after etcd/pull/12933. With the caching mechanism for read transactions, the transaction throughput is increased up to 1.4 times.

Figure 6: etcd transaction ratio with a high read ratio. The value at the top is the ratio of reads and writes. The first ratio, 4.0, is 4 reads per 1 write. The second ratio, 8.0, is 8 reads per 1 write. The value at the right bar represents the inverse ratio of transaction throughput before and after etcd/pull/12933. With the caching mechanism for read transactions, the transaction throughput is increased up to 2.5 times.

Long-running load tests revealed that etcd server misrepresented its real memoryusage by masking the impact of Go garbage collection. We discovered that etcd server with Go 1.12 changed the runtime to use MADV_FREE in Linux kernel, and as a result, reclaimed memory was notreflected in the resident set size, or RSS, metric. This had made the etcd memoryusage metric inaccurately static, thus showing no sign of Go garbage collection.To fix this monitoring problem, we compile etcd 3.5 with Go 1.16 that defaultsto MADV_DONTNEED on Linux. For more information, see Figure 7 and GitHub Go issue 42330.

Figure 7: etcd memory usage during range query before and after setting MADV_DONTNEED in Go runtime. When run with GODEBUG=madvdontneed=1" or Go v1.16 or later, the etcd server accurately reports its memory usage in the CloudWatch mem_used metric or other monitoring tools such as top.

Monitoring is a fundamental service for reliability and observability. Monitoringenables individual service owners to understand the current state and identifypossible causes for problem reports. Known as telemetry, the goal is to detect early warning signs anddiagnose potential issues. etcd creates server logs with tracinginformation and publishes Prometheus metrics.

Distributed systems are full of subtle edge cases. The fact that a bug may onlyemerge under special circumstances warrants exhaustive test coverage beyondsimple unit testing. etcd runs integration, end-to-end, and failure injectiontests, which provide a reliable and faster way to validate each change. However,as development continued with extended feature sets, flaky tests quickly piledup draining our productivity. So, we took on the series of arduous tasks thatoften required multiple hours of debugging to root cause of failures toimprove test quality. Some notable changes include the following:

etcd presubmit tests are now fast and reliable, but were mostly running on x86processors. And there have been numerous requests to support other architectureslike ARM (see GitHub issue 12852) ands390x (see GitHub issue 11163).A self-hosted GitHub action runnerprovides a consistent way of hosting various external test workers (see GitHubissue 12856). Using the GitHubaction, etcd now runs tests on ARM-based AWS EC2 instances (Graviton),thereby officially supporting ARM64 (aarch64) platform.In addition, we introduced a mechanism to support other platforms andcategorized support tiers based on testing coverage. For more information,see the Supported platforms documentation PR 273 and the Supported platforms documentation.

To better support integration with external projects, etcd now fullyadopts the Go 1.16 module. Thisbrought challenges as the existing codebase made migrationarduous, causing concerns regarding adoption in the community). Tooling is an importantpart of etcd development and as a result, we needed a better solution to support our contributor experience.

To support inclusive naming initiatives, etcdprojects renamed the default branch master to main (see etcd-io/etcdchange and etcd-io/websitechange). The migration wasseamless as GitHub handles the necessary redirects (see GitHubrenaming).

The diversity of etcd end users keeps expanding: Cloudflarerelies on etcd for managing its data center,Grafana Cortex stores its configuration data in etcd,Netflix Titus uses etcd for managing its container workloads,and Tailscaleruns its control plane on top of etcd.

Since etcd joined Cloud Native Computing Foundation(CNCF) in December 2018, we haverefactored all user-facing documentation into a dedicated repositoryetcd-io/website and modernized its websitehosting with Hugo). The migration was a hugeundertaking that required multiple months of engineering efforts andcommunication between maintainers. The very blog post you are reading now ishosted on the new etcd.io, thanks tolucperkins@,chalin@ of CNCF,nate-double-u@ of CNCF, and many othercommunity contributors. 006ab0faaa