* Add fixes for failure in specialization
* reduce specialization in progress and remove expired requests from queue when specialization is timed out
* rename markSpecializationFailure and remove logger from the queue
* refactor clean up code in api.go and add test case for queue
Details:
- Cleanup svc waiting for the counter in the pool manager if specialization fails
- Cleanup active requests counter in pool manager if client exists the demand for function service while we have allocated function service
- Consider specialization timeout if pod ready timeout > specialization timeout in waiting for ready pod. We also consider if the request to choosePod is cancelled.
- We ensure if we have requests waiting for service requests but if there is no pod in the specialization we clean up those.
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Signed-off-by: Sanket Sudake <sanketsudake@gmail.com>
Co-authored-by: Pranoy Kundu <pranoy1998k@gmail.com>
* add functionality to wait for specialization by keeping track of incoming requests
* format executor package
* fix required capacity to specialise new pod condition
* move handling concurrency logic into pool cache from executor
* remove unused methods and structs
* implement queue in to store the svc wait
* create a queue struct and its methods to handle concurrent inputs
* use newly created queue to store waiting for svc requests
* add waiting requests in queue and use them when a svc is ready
* set function to request in queue if the context is still alive
* remove concurrency approach to set svc for waiting requests
* update the active requests whenever requests from pool are assigned a svc
* add doc to define why the conditions exist
* remove unwanted params in strcut and clean up code
* set error while getting svc value if sum of specialization in progress and specialized is only more than concurrency limit
* remove duplicate functions and unnecessary values in struct
* close svc channel on set value and create constants for default concurrency and rpp
* get next value in queue in case context is timed out for fetched value
* remove specializationInProgress counter from pool cache
* return in case the queue is empty wihle setting func to svc
* test getSvcVaue and setSvcValue in poolcache
* add unit tests for GetConcurrent and GetRequestsPerPod methods
* reorder imports
* add fuzzy testing for getSVCValue and setSVCValue in poolcache
* restructure go mod file and update pool cache test cases
* Add tests and bug fixes
* refactor code and add test cases
* add svcWaiting check while setting svc value
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Signed-off-by: Sanket Sudake <sanketsudake@gmail.com>
Co-authored-by: Sanket Sudake <sanketsudake@gmail.com>
* Created separate file for authmiddleware fn
* Optimize auth login and middleware
* Added unittests for authmiddleware
* Fixed authURL
* Removed featureConfig as global variable
* Fix integration test according to examples repo changes
* Fix integration test path for go module-example
Co-authored-by: Sanket Sudake <sanketsudake@gmail.com>
* Defining httpserver package to capture httpserver shutdown and
introduces uniform running of http server across codebase.
* Add unit tests for httpserver
Signed-off-by: Sanket Sudake <sanketsudake@gmail.com>
- Enabled metrics in storagesvc, buildermgr and controller.
- Added a middleware in storagesvc, router, executor and controller to monitor total number of http requests, each request's duration and number of requests that are currently being served. These requests can be filtered on their path, method or statuscode.
- Removed functionCallDuration and functionCallResponseSize metrics from router.
- Removed funcAliveSummary, funcIsAlive, funcReapTime and idleTime metrics.
- Replaced function calls for collecting metrics to direct metric calls.
Signed-off-by: Sanket Sudake <sanketsudake@gmail.com>
Co-authored-by: Sanket Sudake <sanketsudake@gmail.com>
The io/ioutil package has been deprecated as of Go 1.16, see
https://golang.org/doc/go1.16#ioutil. This commit replaces the existing
io/ioutil functions with their new definitions in io and os packages.
Signed-off-by: Eng Zer Jun <engzerjun@gmail.com>
* Capture important open telemetry events with span in fission
* Add context to missing HTTP calls
* Add Trace ID in logs
* capture trace id in the proxy handler function
* Always registry tracer to get traceID
Signed-off-by: Sanket Sudake <sanketsudake@gmail.com>
* add opentracing section and otelCollectorEndpoint
* initialize OTLP exporter
* pkg/controller: changes for context propagation
* pkg/executor: changes for context propagation
* pkg/fetcher: changes for context propagation
* pkg/router: changes for context propagation
* pkg/storagesvc: changes for context propagation
* set no default value for otel collector endpoint
* update readme and add notes to charts
* move common code to pkg/utils/otel
* adding fn and env as attributes
* don't use otelhttp transport for websocket
* URL ignore with common filter UrlsToIgnore
Note: The web socket example does not work when using OTEL HTTP. Here is an issue related to that on open-telemetry/opentelemetry-js-contrib.
Signed-off-by: Gaurav Gahlot <gauravgahlot0107@gmail.com>
Co-authored-by: Sanket Sudake <sanketsudake@gmail.com>
PR adds a new executortype which supports running containers as functions. New CLI under functions is added to create container as functions.
Co-authored-by: Harsh Thakur <harshthakur9030@gmail.com>
Co-authored-by: Sanket Sudake <sanketsudake@gmail.com>
Adding once only execution pattern to pool manager based functions. This is for use cases where you don't want to share the samne pod for another execution instance!
Increase the default concurrency to 500 from 5 set in the function. Usually, it is good to error on the higher side and if needed, users can always fine-tune it to their needs.
This feature enables routing more than one request to a pod at the same time. This is the first draft of the work and might involve more optimizations later.
Passing information of function from router to executor is more efficient than calling the K8S API. This change does that instead of passing only metadata and then executor calling the K8S API again.
A ready pod which can be specialized was fetched for every function earlier, this has been changed to a queue and cache implementation in client-go to improve performance.
Poolmanager when tested at high load had some issues and this PR fixes one set of them which were found so far.
Co-authored-by: Vishal <vishal-biyani@users.noreply.github.com>
Concurrency in the pool manager allows specializing pods concurrently based on a specified limit.
Co-authored-by: Vishal <vishal-biyani@users.noreply.github.com>
Previously, once the executor is deleted for reasons (like upgrade or cluster scale-in),
the new executor deletes all existing resources created by the old executor and creates
new one. This mechanism becomes a problem when there are requests connecting to the
existing pods. Also in the worst case, the cluster may not have enough resources to create
new pods and cause service downtime.
This PR let each executor type adopts existing resources before starting the executor
API services, and so the alive connections won't experience failure. However, the requests
send to the function that doesn't have alive function pods will still fail due to the
executor is in bootstrapping.
The pool manager keeps terminating function pod periodically even there are
traffic to the function. The root cause is that executor, poolmgr, newdeploy
manage their own functionServiceCache separately. And when router taps a
function, executor updates the access time of the function service entry in its
own cache without notifying executor types to do the update as well. Hence,
the access time of function service entry in poolmanager cache never gets updated.
Due to the access time never gets updated, the idle pod reaper in poolmanager
then thinks the function pod is in idle state and recycle it.
This PR removes the cache in executor itself, and when router tries to tap a function,
executor will call executor type to tap the function and update access time.
The router taps function service one by one which is inefficient and
increases the burden of executor. This PR aggregates all requests into
one to solve the problem mentioned above.
* Config and secret change to invoke function update
* Added recycle function for pool manager as well - where it recycles the specialized pods
* Switched to rolling update of pods and env variable based change instead of deleting pods in new deploy executor
This PR removes not so useful logs and changes most of Info level
log to Debug/Error level in hot path while preserving some of them
that is helpful for troubleshooting.
