Current implementation retries forever until our
log buffer is full, and we start dropping events.
This PR allows you to set a value until we give
up on existing audit/logger batches to proceed to
process the new ones.
Bonus:
- do not blow up buffers beyond batchSize value
- do not leak the ticker if the worker returns
The items will be saved per target batch and will
be committed to the queue store when the batch is full
Also, periodically commit the batched items to the queue store
based on configured commit_timeout; default is 30s;
Bonus: compress queue store multi writes
without atomic load() it is possible that for
a slow receiver we would get into a hot-loop, when
logCh is full and there are many incoming callers.
to avoid this as a workaround enable BATCH_SIZE
greater than 100 to ensure that your slow receiver
receives data in bulk to avoid being throttled in
some manner.
this PR however fixes the unprotected access to
the current workers value.
This change uses the updated ldap library in minio/pkg (bumped
up to v3). A new config parameter is added for LDAP configuration to
specify extra user attributes to load from the LDAP server and to store
them as additional claims for the user.
A test is added in sts_handlers.go that shows how to access the LDAP
attributes as a claim.
This is in preparation for adding SSH pubkey authentication to MinIO's SFTP
integration.
Create new code paths for multiple subsystems in the code. This will
make maintaing this easier later.
Also introduce bugLogIf() for errors that should not happen in the first
place.
- old version was unable to retain messages during config reload
- old version could not go from memory to disk during reload
- new version can batch disk queue entries to single for to reduce I/O load
- error logging has been improved, previous version would miss certain errors.
- logic for spawning/despawning additional workers has been adjusted to trigger when half capacity is reached, instead of when the log queue becomes full.
- old version would json marshall x2 and unmarshal 1x for every log item. Now we only do marshal x1 and then we GetRaw from the store and send it without having to re-marshal.
configure batch size to send audit/logger events
in batches instead of sending one event per connection.
this is mainly to optimize the number of requests
we make to webhook endpoint.
simplify audit webhook worker model
fixes couple of bugs like
- ping(ctx) was creating a logger without updating
number of workers leading to incorrect nWorkers
scaling, causing an additional worker that is not
tracked properly.
- h.logCh <- entry could potentially hang for when
the queue is full on heavily loaded systems.
there can be a sudden spike in tiny allocations,
due to too much auditing being done, also don't hang
on the
```
h.logCh <- entry
```
after initializing workers if you do not have a way to
dequeue for some reason.
Add a new function logger.Event() to send the log to Console and
http/kafka log webhooks. This will include some internal events such as
disk healing and rebalance/decommissioning
This PR adds a WebSocket grid feature that allows servers to communicate via
a single two-way connection.
There are two request types:
* Single requests, which are `[]byte => ([]byte, error)`. This is for efficient small
roundtrips with small payloads.
* Streaming requests which are `[]byte, chan []byte => chan []byte (and error)`,
which allows for different combinations of full two-way streams with an initial payload.
Only a single stream is created between two machines - and there is, as such, no
server/client relation since both sides can initiate and handle requests. Which server
initiates the request is decided deterministically on the server names.
Requests are made through a mux client and server, which handles message
passing, congestion, cancelation, timeouts, etc.
If a connection is lost, all requests are canceled, and the calling server will try
to reconnect. Registered handlers can operate directly on byte
slices or use a higher-level generics abstraction.
There is no versioning of handlers/clients, and incompatible changes should
be handled by adding new handlers.
The request path can be changed to a new one for any protocol changes.
First, all servers create a "Manager." The manager must know its address
as well as all remote addresses. This will manage all connections.
To get a connection to any remote, ask the manager to provide it given
the remote address using.
```
func (m *Manager) Connection(host string) *Connection
```
All serverside handlers must also be registered on the manager. This will
make sure that all incoming requests are served. The number of in-flight
requests and responses must also be given for streaming requests.
The "Connection" returned manages the mux-clients. Requests issued
to the connection will be sent to the remote.
* `func (c *Connection) Request(ctx context.Context, h HandlerID, req []byte) ([]byte, error)`
performs a single request and returns the result. Any deadline provided on the request is
forwarded to the server, and canceling the context will make the function return at once.
* `func (c *Connection) NewStream(ctx context.Context, h HandlerID, payload []byte) (st *Stream, err error)`
will initiate a remote call and send the initial payload.
```Go
// A Stream is a two-way stream.
// All responses *must* be read by the caller.
// If the call is canceled through the context,
//The appropriate error will be returned.
type Stream struct {
// Responses from the remote server.
// Channel will be closed after an error or when the remote closes.
// All responses *must* be read by the caller until either an error is returned or the channel is closed.
// Canceling the context will cause the context cancellation error to be returned.
Responses <-chan Response
// Requests sent to the server.
// If the handler is defined with 0 incoming capacity this will be nil.
// Channel *must* be closed to signal the end of the stream.
// If the request context is canceled, the stream will no longer process requests.
Requests chan<- []byte
}
type Response struct {
Msg []byte
Err error
}
```
There are generic versions of the server/client handlers that allow the use of type
safe implementations for data types that support msgpack marshal/unmarshal.
Currently, once the audit becomes offline, there is no code that tries
to reconnect to the audit, at the same time Send() quickly returns with
an error without really trying to send a message the audit endpoint; so
the audit endpoint will never be online again.
Fixing this behavior; the current downside is that we miss printing some
logs when the audit becomes offline; however this information is
available in prometheus
Later, we can refactor internal/logger so the http endpoint can send errors to
console target.
If target went offline while MinIO was down, error once
while trying to send message. If target goes offline during
MinIO server running, it already comes through ping() call
and errors out if target offline.
Signed-off-by: Shubhendu Ram Tripathi <shubhendu@minio.io>
all retries must not be counted as failed messages,
a failed message is a single counter not for all
retries, this PR fixes this.
Also we do not need to retry 10-times, instead we should
retry at max 3 times with some jitter to deliver the
messages.
Keys are helpful to ensure the strict ordering of messages, however currently the
code uses a random request id for every log, hence using the request-id
as a Kafka key is not serve any purpose;
This commit removes the usage of the key, to also fix the audit issue from
internal subsystem that does not have a request ID.
Send() is synchronous and can affect the latency of S3 requests when the
logger buffer is full.
Avoid checking if the HTTP target is online or not and increase the
workers anyway since the buffer is already full.
Also, avoid logs flooding when the audit target is down.
