Both Azure & S3 gateways call for object information before returning
the stream of the object, however, the object content/length could be
modified meanwhile, which means it can return a corrupted object.
Use ETag to ensure that the object was not modified during the GET call
AZURE_STORAGE_ACCOUNT and AZURE_STORAGE_KEY are used in
azure CLI to specify the azure blob storage access & secret keys. With this commit,
it is possible to set them if you want the gateway's own credentials to be
different from the Azure blob credentials.
Co-authored-by: Harshavardhana <harsha@minio.io>
This is to ensure that Go contexts work properly, after some
interesting experiments I found that Go net/http doesn't
cancel the context when Body is non-zero and hasn't been
read till EOF.
The following gist explains this, this can lead to pile up
of go-routines on the server which will never be canceled
and will die at a really later point in time, which can
simply overwhelm the server.
https://gist.github.com/harshavardhana/c51dcfd055780eaeb71db54f9c589150
To avoid this refactor the locking such that we take locks after we
have started reading from the body and only take locks when needed.
Also, remove contextReader as it's not useful, doesn't work as expected
context is not canceled until the body reaches EOF so there is no point
in wrapping it with context and putting a `select {` on it which
can unnecessarily increase the CPU overhead.
We will still use the context to cancel the lockers etc.
Additional simplification in the locker code to avoid timers
as re-using them is a complicated ordeal avoid them in
the hot path, since locking is very common this may avoid
lots of allocations.
In `(*cacheObjects).GetObjectNInfo` copy the metadata before spawning a goroutine.
Clean up a few map[string]string copies as well, reducing allocs and simplifying the code.
Fixes#10426
Without instantiating a new rest client we can
have a recursive error which can lead to
healthcheck returning always offline, this can
prematurely take the servers offline.
- Implement a new xl.json 2.0.0 format to support,
this moves the entire marshaling logic to POSIX
layer, top layer always consumes a common FileInfo
construct which simplifies the metadata reads.
- Implement list object versions
- Migrate to siphash from crchash for new deployments
for object placements.
Fixes#2111
Advantages avoids 100's of stats which are needed for each
upload operation in FS/NAS gateway mode when uploading a large
multipart object, dramatically increases performance for
multipart uploads by avoiding recursive calls.
For other gateway's simplifies the approach since
azure, gcs, hdfs gateway's don't capture any specific
metadata during upload which needs handler validation
for encryption/compression.
Erasure coding was already optimized, additionally
just avoids small allocations of large data structure.
Fixes#7206
This PR is to ensure that we call the relevant object
layer APIs for necessary S3 API level functionalities
allowing gateway implementations to return proper
errors as NotImplemented{}
This allows for all our tests in mint to behave
appropriately and can be handled appropriately as
well.
- Add conservative timeouts upto 3 minutes
for internode communication
- Add aggressive timeouts of 30 seconds
for gateway communication
Fixes#9105Fixes#8732Fixes#8881Fixes#8376Fixes#9028
To allow better control the cache eviction process.
Introduce MINIO_CACHE_WATERMARK_LOW and
MINIO_CACHE_WATERMARK_HIGH env. variables to specify
when to stop/start cache eviction process.
Deprecate MINIO_CACHE_EXPIRY environment variable. Cache
gc sweeps at 30 minute intervals whenever high watermark is
reached to clear least recently accessed entries in the cache
until sufficient space is cleared to reach the low watermark.
Garbage collection uses an adaptive file scoring approach based
on last access time, with greater weights assigned to larger
objects and those with more hits to find the candidates for eviction.
Thanks to @klauspost for this file scoring algorithm
Co-authored-by: Klaus Post <klauspost@minio.io>
Metrics used to have its own code to calculate offline disks.
StorageInfo() was avoided because it is an expensive operation
by sending calls to all nodes.
To make metrics & server info share the same code, a new
argument `local` is added to StorageInfo() so it will only
query local disks when needed.
Metrics now calls StorageInfo() as server info handler does
but with the local flag set to false.
Co-authored-by: Praveen raj Mani <praveen@minio.io>
Co-authored-by: Harshavardhana <harsha@minio.io>
We added support for caching and S3 related metrics in #8591. As
a continuation, it would be helpful to add support for Azure & GCS
gateway related metrics as well.
This is to avoid making calls to backend and requiring
gateways to allow permissions for ListBuckets() operation
just for Liveness checks, we can avoid this and make
our liveness checks to be more performant.
- adding oauth support to MinIO browser (#8400) by @kanagaraj
- supports multi-line get/set/del for all config fields
- add support for comments, allow toggle
- add extensive validation of config before saving
- support MinIO browser to support proper claims, using STS tokens
- env support for all config parameters, legacy envs are also
supported with all documentation now pointing to latest ENVs
- preserve accessKey/secretKey from FS mode setups
- add history support implements three APIs
- ClearHistory
- RestoreHistory
- ListHistory
- add help command support for each config parameters
- all the bug fixes after migration to KV, and other bug
fixes encountered during testing.
On objects bigger than 100MiB can have a corrupted object
stored due to partial blockListing attempted right after
each blocks uploaded. Simplify this code to ensure that
all the blocks successfully uploaded are committed right
away.
This PR also updates the azure-sdk-go to latest release.
The fix in #7646 introduced a regression which
was left unnoticed, the fix didn't work for
sub-commands unfortunately. This fixes it
by moving v1.21.0 version of the minio/cli
package.
Fixes#7924
Bulk delete at storage level in Multiple Delete Objects API
In order to accelerate bulk delete in Multiple Delete objects API,
a new bulk delete is introduced in storage layer, which will accept
a list of objects to delete rather than only one. Consequently,
a new API is also need to be added to Object API.
Anis Elleuch