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Boxiang Sun
gitlab-ce
Commits
be499414
Commit
be499414
authored
Sep 04, 2018
by
Evan Read
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Make cache vs artifacts section more visible, and minor enhancements to text.
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doc/ci/caching/index.md
View file @
be499414
...
@@ -14,6 +14,64 @@ starting from GitLab 9.0.
...
@@ -14,6 +14,64 @@ starting from GitLab 9.0.
Make sure you read the
[
`cache` reference
](
../yaml/README.md#cache
)
to learn
Make sure you read the
[
`cache` reference
](
../yaml/README.md#cache
)
to learn
how it is defined in
`.gitlab-ci.yml`
.
how it is defined in
`.gitlab-ci.yml`
.
## Cache vs artifacts
NOTE:
**Note:**
Be careful if you use cache and artifacts to store the same path in your jobs
as
**caches are restored before artifacts**
and the content would be overwritten.
Don't mix the caching with passing artifacts between stages. Caching is not
designed to pass artifacts between stages. Cache is for runtime dependencies
needed to compile the project:
-
`cache`
-
**Use for temporary storage for project dependencies.**
Not useful
for keeping intermediate build results, like
`jar`
or
`apk`
files.
Cache was designed to be used to speed up invocations of subsequent runs of a
given job, by keeping things like dependencies (e.g., npm packages, Go vendor
packages, etc.) so they don't have to be re-fetched from the public internet.
While the cache can be abused to pass intermediate build results between stages,
there may be cases where artifacts are a better fit.
-
`artifacts`
-
**Use for stage results that will be passed between stages.**
Artifacts were designed to upload some compiled/generated bits of the build,
and they can be fetched by any number of concurrent Runners. They are
guaranteed to be available and are there to pass data between jobs. They are
also exposed to be downloaded from the UI.
**
Artifacts can only exist in
directories relative to the build directory
**
and specifying paths which don't
comply to this rule trigger an unintuitive and illogical error message (an
enhancement is discussed at
https://gitlab.com/gitlab-org/gitlab-ce/issues/15530). Artifacts need to be
uploaded to the GitLab instance (not only the GitLab runner) before the next
stage job(s) can start, so you need to evaluate carefully whether your
bandwidth allows you to profit from parallelization with stages and shared
artifacts before investing time in changes to the setup.
It's sometimes confusing because the name artifact sounds like something that
is only useful outside of the job, like for downloading a final image. But
artifacts are also available in between stages within a pipeline. So if you
build your application by downloading all the required modules, you might want
to declare them as artifacts so that each subsequent stage can depend on them
being there. There are some optimizations like declaring an
[
expiry time
](
../yaml/README.md#artifacts-expire_in
)
so you don't keep artifacts
around too long, and using
[
dependencies
](
../yaml/README.md#dependencies
)
to
control exactly where artifacts are passed around.
In summary:
-
Caches are disabled if not defined globally or per job (using
`cache:`
)
-
Caches are available for all jobs in your
`.gitlab-ci.yml`
if enabled globally
-
Caches can be used by subsequent pipelines of that very same job (a script in
a stage) in which the cache was created (if not defined globally).
-
Caches are stored where the Runner is installed
**and**
uploaded to S3 if
[
distributed cache is enabled
](
https://docs.gitlab.com/runner/configuration/autoscale.html#distributed-runners-caching
)
-
Caches defined per job are only used either a) for the next pipeline of that job,
or b) if that same cache is also defined in a subsequent job of the same pipeline
-
Artifacts are disabled if not defined per job (using
`artifacts:`
)
-
Artifacts can only be enabled per job, not globally
-
Artifacts are created during a pipeline and can be used by the subsequent
jobs of that currently active pipeline
-
Artifacts are always uploaded to GitLab (known as coordinator)
-
Artifacts can have an expiration value for controlling disk usage (30 days by default).
## Good caching practices
## Good caching practices
We have the cache from the perspective of the developers (who consume a cache
We have the cache from the perspective of the developers (who consume a cache
...
@@ -467,60 +525,3 @@ Behind the scenes, this works by increasing a counter in the database, and the
...
@@ -467,60 +525,3 @@ Behind the scenes, this works by increasing a counter in the database, and the
value of that counter is used to create the key for the cache by appending an
value of that counter is used to create the key for the cache by appending an
integer to it:
`-1`
,
`-2`
, etc. After a push, a new key is generated and the
integer to it:
`-1`
,
`-2`
, etc. After a push, a new key is generated and the
old cache is not valid anymore.
old cache is not valid anymore.
## Cache vs artifacts
NOTE:
**Note:**
Be careful if you use cache and artifacts to store the same path in your jobs
as
**caches are restored before artifacts**
and the content would be overwritten.
Don't mix the caching with passing artifacts between stages. Caching is not
designed to pass artifacts between stages. Cache is for runtime dependencies
needed to compile the project:
-
`cache`
-
**Use for temporary storage for project dependencies.**
Not useful
for keeping intermediate build results, like
`jar`
or
`apk`
files.
Cache was designed to be used to speed up invocations of subsequent runs of a
given job, by keeping things like dependencies (e.g., npm packages, Go vendor
packages, etc.) so they don't have to be re-fetched from the public internet.
While the cache can be abused to pass intermediate build results between stages,
there may be cases where artifacts are a better fit.
-
`artifacts`
-
**Use for stage results that will be passed between stages.**
Artifacts were designed to upload some compiled/generated bits of the build,
and they can be fetched by any number of concurrent Runners. They are
guaranteed to be available and are there to pass data between jobs. They are
also exposed to be downloaded from the UI.
**
Artifacts can only exist in
directories relative to the build directory
**
and specifying paths which don't
comply to this rule trigger an unintuitive and unlogical error message (an
enhancement is discussed at
https://gitlab.com/gitlab-org/gitlab-ce/issues/15530). Artifacts need to be
uploaded to the GitLab instance (not only the GitLab runner) before the next
stage job(s) can start, so you need to evaluate carefully whether your
bandwidth allows you to profit from parallelization with stages and shared
artifacts before investing time in changes to the setup.
It's sometimes confusing because the name artifact sounds like something that
is only useful outside of the job, like for downloading a final image. But
artifacts are also available in between stages within a pipeline. So if you
build your application by downloading all the required modules, you might want
to declare them as artifacts so that each subsequent stage can depend on them
being there. There are some optimizations like declaring an
[
expiry time
](
../yaml/README.md#artifacts-expire_in
)
so you don't keep artifacts
around too long, and using
[
dependencies
](
../yaml/README.md#dependencies
)
to
control exactly where artifacts are passed around.
So, to sum up:
-
Caches are disabled if not defined globally or per job (using
`cache:`
)
-
Caches are available for all jobs in your
`.gitlab-ci.yml`
if enabled globally
-
Caches can be used by subsequent pipelines of that very same job (a script in
a stage) in which the cache was created (if not defined globally).
-
Caches are stored where the Runner is installed
**and**
uploaded to S3 if
[
distributed cache is enabled
](
https://docs.gitlab.com/runner/configuration/autoscale.html#distributed-runners-caching
)
-
Caches defined per job are only used either a) for the next pipeline of that job,
or b) if that same cache is also defined in a subsequent job of the same pipeline
-
Artifacts are disabled if not defined per job (using
`artifacts:`
)
-
Artifacts can only be enabled per job, not globally
-
Artifacts are created during a pipeline and can be used by the subsequent
jobs of that currently active pipeline
-
Artifacts are always uploaded to GitLab (known as coordinator)
-
Artifacts can have an expiration value for controlling disk usage (30 days by default)
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