> - **Performance tested daily with the [GitLab Performance Tool](https://gitlab.com/gitlab-org/quality/performance)**:
> - **Validation and test results:** The Quality Engineering team does [regular smoke and performance tests](index.md#validation-and-test-results) to ensure the reference architectures remain compliant
> - **Cloud Native Hybrid:** No. For a cloud native hybrid environment, you
> can follow a [modified hybrid reference architecture](#cloud-native-hybrid-reference-architecture-with-helm-charts).
> - **Performance tested daily with the [GitLab Performance Tool (GPT)](https://gitlab.com/gitlab-org/quality/performance)**:
> - **Validation and test results:** The Quality Engineering team does [regular smoke and performance tests](index.md#validation-and-test-results) to ensure the reference architectures remain compliant
> - **Performance tested weekly with the [GitLab Performance Tool (GPT)](https://gitlab.com/gitlab-org/quality/performance)**:
> - **Validation and test results:** The Quality Engineering team does [regular smoke and performance tests](index.md#validation-and-test-results) to ensure the reference architectures remain compliant
> - **Performance tested daily with the [GitLab Performance Tool (GPT)](https://gitlab.com/gitlab-org/quality/performance)**:
> - **Validation and test results:** The Quality Engineering team does [regular smoke and performance tests](index.md#validation-and-test-results) to ensure the reference architectures remain compliant
> - **Performance tested weekly with the [GitLab Performance Tool (GPT)](https://gitlab.com/gitlab-org/quality/performance)**:
> - **Validation and test results:** The Quality Engineering team does [regular smoke and performance tests](index.md#validation-and-test-results) to ensure the reference architectures remain compliant
> - **Performance tested weekly with the [GitLab Performance Tool (GPT)](https://gitlab.com/gitlab-org/quality/performance)**:
> - **Validation and test results:** The Quality Engineering team does [regular smoke and performance tests](index.md#validation-and-test-results) to ensure the reference architectures remain compliant
> - **Performance tested weekly with the [GitLab Performance Tool (GPT)](https://gitlab.com/gitlab-org/quality/performance)**:
> - **Validation and test results:** The Quality Engineering team does [regular smoke and performance tests](index.md#validation-and-test-results) to ensure the reference architectures remain compliant
at specific coded workloads, and the throughputs used for testing were
calculated based on sample customer data. Select the
[reference architecture](#available-reference-architectures) that matches your scale.
Each endpoint type is tested with the following number of requests per second (RPS)
per 1,000 users:
- API: 20 RPS
- Web: 2 RPS
- Git (Pull): 2 RPS
- Git (Push): 0.4 RPS (rounded to nearest integer)
For GitLab instances with less than 2,000 users, it's recommended that you use
the [default setup](#automated-backups) by
[installing GitLab](../../install/index.md) on a single machine to minimize
...
...
@@ -48,7 +34,8 @@ When scaling GitLab, there are several factors to consider:
- A load balancer is added in front to distribute traffic across the application nodes.
- The application nodes connects to a shared file server and PostgreSQL and Redis services on the backend.
NOTE:
## Available reference architectures
Depending on your workflow, the following recommended reference architectures
may need to be adapted accordingly. Your workload is influenced by factors
including how active your users are, how much automation you use, mirroring,
...
...
@@ -57,12 +44,10 @@ provided by [GCP machine types](https://cloud.google.com/compute/docs/machine-ty
For different cloud vendors, attempt to select options that best match the
provided architecture.
## Available reference architectures
The following reference architectures are available.
### GitLab package (Omnibus)
The following reference architectures, where the GitLab package is used, are available:
-[Up to 1,000 users](1k_users.md)
-[Up to 2,000 users](2k_users.md)
-[Up to 3,000 users](3k_users.md)
...
...
@@ -87,17 +72,53 @@ to get assistance from Support with troubleshooting the [2,000 users](2k_users.m
and higher reference architectures.
[Read more about our definition of scaled architectures](https://about.gitlab.com/support/#definition-of-scaled-architecture).
### Validation and test results
## Validation and test results
The [Quality Engineering team](https://about.gitlab.com/handbook/engineering/quality/quality-engineering/)
does regular smoke and performance tests for the reference architectures to ensure they
remain compliant.
### Why we perform the tests
The Quality Department has a focus on measuring and improving the performance
of GitLab, as well as creating and validating reference architectures that
self-managed customers can rely on as performant configurations.
For more information, see our [handbook page](https://about.gitlab.com/handbook/engineering/quality/performance-and-scalability/).
The [Quality Engineering - Enablement team](https://about.gitlab.com/handbook/engineering/quality/quality-engineering/) does regular smoke and performance tests for the reference architectures to ensure they remain compliant.
### How we perform the tests
- Testing occurs against all reference architectures and cloud providers in an automated and ad-hoc fashion. This is done by two tools:
- The [GitLab Environment Toolkit](https://gitlab.com/gitlab-org/gitlab-environment-toolkit) for building the environments.
- The [GitLab Performance Tool](https://gitlab.com/gitlab-org/quality/performance) for performance testing.
- Network latency on the test environments between components on all Cloud Providers were measured at <5ms. Note that this is shared as an observation and not as an implicit recommendation.
- We aim to have a "test smart" approach where architectures tested have a good range that can also apply to others. Testing focuses on 10k Omnibus on GCP as the testing has shown this is a good bellwether for the other architectures and cloud providers as well as Cloud Native Hybrids.
- Testing is done publicly and all results are shared.
- For more information about performance testing at GitLab, read [how our QA team leverages GitLab’s performance testing tool (and you can too)](https://about.gitlab.com/blog/2020/02/18/how-were-building-up-performance-testing-of-gitlab/).
Testing occurs against all reference architectures and cloud providers in an automated and ad-hoc fashion. This is done by two tools:
- The [GitLab Environment Toolkit](https://gitlab.com/gitlab-org/gitlab-environment-toolkit) for building the environments.
- The [GitLab Performance Tool](https://gitlab.com/gitlab-org/quality/performance) for performance testing.
Network latency on the test environments between components on all Cloud Providers were measured at <5ms. Note that this is shared as an observation and not as an implicit recommendation.
We aim to have a "test smart" approach where architectures tested have a good range that can also apply to others. Testing focuses on 10k Omnibus on GCP as the testing has shown this is a good bellwether for the other architectures and cloud providers as well as Cloud Native Hybrids.
The Standard Reference Architectures are designed to be platform agnostic, with everything being run on VMs via [Omnibus GitLab](https://docs.gitlab.com/omnibus/). While testing occurs primarily on GCP, ad-hoc testing has shown that they perform similarly on equivalently specced hardware on other Cloud Providers or if run on premises (bare-metal).
Testing on these reference architectures is performed with the
at specific coded workloads, and the throughputs used for testing are
calculated based on sample customer data. Select the
[reference architecture](#available-reference-architectures) that matches your scale.
Each endpoint type is tested with the following number of requests per second (RPS)
per 1,000 users:
- API: 20 RPS
- Web: 2 RPS
- Git (Pull): 2 RPS
- Git (Push): 0.4 RPS (rounded to nearest integer)
### How to interpret the results
NOTE:
Read our blog post on [how our QA team leverages GitLab’s performance testing tool](https://about.gitlab.com/blog/2020/02/18/how-were-building-up-performance-testing-of-gitlab/).
Testing is done publicly and all results are shared.
The following table details the testing done against the reference architectures along with the frequency and results. Additional testing is continuously evaluated, and the table is updated accordingly.
...
...
@@ -192,9 +213,7 @@ table.test-coverage th {
</tr>
</table>
The Standard Reference Architectures are designed to be platform agnostic, with everything being run on VMs via [Omnibus GitLab](https://docs.gitlab.com/omnibus/). While testing occurs primarily on GCP, ad-hoc testing has shown that they perform similarly on equivalently specced hardware on other Cloud Providers or if run on premises (bare-metal).
### Cost to run
## Cost to run
<tableclass="test-coverage">
<col>
...
...
@@ -271,7 +290,7 @@ The Standard Reference Architectures are designed to be platform agnostic, with
</tr>
</table>
### Recommended cloud providers and services
## Recommended cloud providers and services
NOTE:
The following lists are non exhaustive. Generally, other cloud providers not listed
