chore(deps): update all non-major regex dependencies #926
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This PR contains the following updates:
1.61.5->1.61.70.23.0->0.30.11.48.0->1.53.01.14.1->1.15.11.14.4->1.15.43.6.0->3.7.31.9.2->1.9.31.23->1.244.18.1->4.18.31.63.4->1.64.80.7.0->0.8.01.27.0->1.29.00.3.57->0.3.110Warning
Some dependencies could not be looked up. Check the Dependency Dashboard for more information.
Release Notes
air-verse/air (air-verse/air)
v1.61.7Compare Source
What's Changed
New Contributors
Full Changelog: air-verse/air@v1.61.5...v1.61.7
v1.61.6Compare Source
Changelog
ce50989Add exiter to test os.Exit caseauthzed/zed (authzed/zed)
v0.30.1Compare Source
What's Changed
Full Changelog: authzed/zed@v0.30.0...v0.30.1
v0.30.0Compare Source
What's Changed
zed validateby @miparnisari in https://github.com/authzed/zed/pull/478Full Changelog: authzed/zed@v0.29.0...v0.30.0
v0.29.0Compare Source
What's Changed
Full Changelog: authzed/zed@v0.28.0...v0.29.0
v0.28.0Compare Source
Highlights
zed backupzed permission lookup-resourcesWhat's Changed
New Contributors
Full Changelog: authzed/zed@v0.27.0...v0.28.0
v0.27.0Compare Source
What's New
Composable schema support! See documentation here: https://authzed.com/docs/spicedb/modeling/composable-schemas
What's Changed
Full Changelog: authzed/zed@v0.26.0...v0.27.0
v0.26.0Compare Source
What's New
You can now add an expiration to a relationship written by zed with the
--expirationflag:In practice:
What's Changed
Full Changelog: authzed/zed@v0.25.0...v0.26.0
v0.25.0Compare Source
New in this release
--explainto a bulk check call and get the same kind of debug output that you get on a normal check callschemaFilekey in your validation yaml files that references an external schema by path. This allows for a schema file to be kept separate from the validation file without having to manually concatenate.zed validatewith multiple files as arguments. Together with the previous change, this should mean that you can have a folder full of independent validation files that describe separate test cases and all reference the same schema.What's Changed
Full Changelog: authzed/zed@v0.24.0...v0.25.0
v0.24.0Compare Source
What's Changed
New Contributors
Full Changelog: authzed/zed@v0.23.0...v0.24.0
bufbuild/buf (bufbuild/buf)
v1.53.0Compare Source
v1.52.1Compare Source
v1.52.0Compare Source
exclude_typeon a non imported package.--exclude-typeflag forbuf generatewhen an input is specified.buf lintandbuf breakingoutput even when source code info is notavailable. This allows
buf lintandbuf breakingto respectignoreandignore_onlyconfigurations when source code info is not available.
v1.51.0Compare Source
buf convertto allow for zero length forbinpb,txtpb, andyamlformats.--include-typesforbuf generate.--against-registryflag tobuf breakingthat runs breaking checks against the latestcommit on the default branch of the corresponding module in the registry.
buf generate.buf generate. Adds the ability to exclude types with the parameterexclude_typesinbuf.gen.yamland a flag--exclude-typesin the CLI.Type filters may now also be specified as plugin parameters in
buf.gen.yaml.v1.50.1Compare Source
v1.50.0Compare Source
filterfor use with git inputs. This sets the filterflag argument for the git fetch command.
v1.49.0Compare Source
buf plugin push --labelto allow pushing a plugin with a label.--digest-changes-onlyflag tobuf registry {module,plugin} commit listto filterout commits that have no digest changes.
buf plugin push --source-control-urlto allow pushing a plugin with the sourcecontrol url.
dapr/cli (dapr/cli)
v1.15.1: Dapr CLI v1.15.1Compare Source
v1.15.0: Dapr CLI v1.15.0Compare Source
dapr/dapr (dapr/dapr)
v1.15.4: Dapr Runtime v1.15.4Compare Source
Dapr 1.15.4
This update includes bug fixes:
Fix degradation of Workflow runtime performance over time
Problem
Running a Workflow app multiple times would cause the performance of the Workflow runtime to degrade significantly over multiple runs.
Impact
Workflow applications would not complete in a timely manner.
Root cause
There was an issue whereby Scheduler client (daprd) connections where not properly pruned from the connection pool for a given Namespace's appID/actorTypes set.
This would lead to jobs/actor reminders being sent to stale client connections that were no longer active.
This caused Jobs to fail, and enter failure policy retry loops.
Solution
Refactor the Scheduler connection pool logic to properly prune stale connections to prevent job execution occurring on stale connections and causing failure policy loops.
Fix remote Actor invocation 500 retry
Problem
An actor invocation across hosts which result in a 500 HTTP header response code would result in the request being retried 5 times.
Impact
Services which return a 500 HTTP header response code would result in requests under normal operation to return slowly, and request the service on the same request multiple times.
Root cause
The Actor engine considered a 500 HTTP header response code to be a retriable error, rather than a successful request which returned a non-200 status code.
Solution
Remove the 500 HTTP header response code from the list of retriable errors.
Problem
Fix Global Actors Enabled Configuration
Problem
When
global.actors.enabledwas set tofalsevia Helm or the environment variableACTORS_ENABLED=false, the Dapr sidecar would still attempt to connect to the placement service, causing readiness probe failures and repeatedly logged errors about failing to connect to placement.Fixes this issue.
Impact
Dapr sidecars would fail their readiness probes and log errors like:
Root cause
The sidecar injector was not properly respecting the global actors enabled configuration when setting up the placement service connection.
Solution
The sidecar injector now properly respects the
global.actors.enabledhelm configuration andACTORS_ENABLEDenvironment variable. When set tofalse, it will not attempt to connect to the placement service, allowing the sidecar to start successfully without actor functionality.Prevent panic of reminder operations on slow Actor Startup
Problem
The Dapr runtime HTTP server would panic if a reminder operation timed out while an Actor was starting up.
Impact
The HTTP server would panic, causing degraded performance.
Root cause
The Dapr runtime would attempt to use the reminder service before it was initialized.
Solution
Correctly return an errors that the actor runtime was not ready in time for the reminder operation.
Remove client-side rate limiter from Sentry
Problem
A cold start of many Dapr deployments would take a long time, and even cause some crash loops.
Impact
A large Dapr deployment would take a non-linear more amount of time that a smaller one to completely roll out.
Root cause
The Sentry Kubernetes client was configured with a rate limiter which would be exhausted when services all new Dapr deployment at once, cause many client to wait significantly.
Solution
Remove the client-side rate limiting from the Sentry Kubernetes client.
Allow Service Account for MetalBear mirrord operator in sidecar injector
Problem
Mirrord Operator is not on the allow list of Service Accounts for the dapr sidecar injector.
Impact
Running mirrord in
copy_targetmode would cause the pod to initalise without the dapr container.Root cause
Mirrord Operator is not on the allow list of Service Accounts for the dapr sidecar injector.
Solution
Add the Mirrord Operator into the allow list of Service Accounts for the dapr sidecar injector.
Fix Scheduler Client connection pruning
Problem
Daprd would attempt to connect to stale Scheduler addresses.
Impact
Network resource usage and error reporting from service mesh sidecars.
Root cause
Daprd would not close Scheduler gRPC connections to hosts which no longer exist.
Solution
Daprd now closes connections to Scheduler hosts when they are no longer in the list of active hosts.
v1.15.3: Dapr Runtime v1.15.3Compare Source
Dapr 1.15.3
This update includes bug fixes:
Fix Timers Deactivating after timer invocation fails
Problem
Fixes this issue.
An app returning a non-2xx status code from a timer invocation would cause a periodic timer to no longer trigger.
Impact
An Actor app which restarted/crashed, or was otherwise busy, would cause a timer to no longer trigger.
This breaks backwards compatibility where a periodic Actor timer would continue to trigger at the defined period, even if the actor was busy or had an error.
Root cause
The Actor timer handle logic deactivates the timer if any timer invocation failed.
Regardless of whether the timer had further ticks defined in it's period schedule.
Solution
As did before v1.15.0, treat any successful or failed timer invocation as the same, and tick the Actor timer forward allowing for future invocations.
Fix Daprd continuously growing in memory
Problem
Fixes an issue where Daprd would continually grow in memory when using Workflows.
Impact
Daprd would eventually use all available memory on the node or cgroup, causing an OOM crash.
Root cause
An internal Actor lock object was not being released from Workflow Activities.
Solution
Release lock memory during Workflow Activity completion.
Fix Scheduler continuously growing in memory
Problem
Scheduler would continuously grow in memory when under heavy usage, for example using Workflows.
Impact
Scheduler would eventually use all available memory on the node or cgroup, causing an OOM crash.
Root cause
Etcd does not automatically Defragment after compaction, causing unused memory to not be released.
Solution
Every 10 minutes, each Scheduler host will check whether the total memory is twice the size of used memory and if so, will defragment that host's Etcd database.
v1.15.2: Dapr Runtime v1.15.2Compare Source
Dapr 1.15.2
This update includes bug fixes:
Fix Actor Invocation from non-Actor hosted Apps
Problem
When invoking an actor from an app which did not have the Actor state store configured, the actor invocation fails.
Impact
Applications were unable to invoke actors if the Actor state store was not scoped for that App ID.
Root cause
If daprd did not have an Actor state store configured, it did not connect to Placement.
This meant it did not have the address for the target Actor.
Solution
Daprd will always attempt to connect to Placement if a Placement address is configured.
Fix Scheduler memory leak
Problem
Scheduler would continually grow in memory during usage.
Impact
Scheduler would consume the entirety of memory on the host machine, or to it's cgroup limit, then OOM crash.
Root cause
A Go routine was doing being closed on connection sends.
Solution
Correctly close the Go routine on completion of the connection send.
v1.15.1: Dapr Runtime v1.15.1Compare Source
Dapr 1.15.1
This update includes bug fixes:
Fix Dapr not honoring max-body-size when invoking actors
Problem
Issue reported here.
When an actor client attempts to invoke an actor with a payload size larger than 4Mb, the call fails with
rpc error: code = ResourceExhausted desc = grpc: received message larger than max.Impact
Users were unable to send actor messages with payloads larger than 4Mb.
Root cause
The Dapr actor gRPC client did not honor the max-body-size parameter that is passed to
daprd.Solution
The Dapr actor gRPC client is configured with the proper gRPC call options.
Fix sending Actor Reentrancy ID HTTP header when disabled
Problem
Calling
this.StateManager.TryGetStateAsync()in the DotNet Actor SDK would return stale data during some invocation scenarios.Impact
The latest Actor state data was not being correctly returned during some Actor invocation scenarios using the DotNet Actor SDK.
Root cause
When Reentrancy was disabled, the Actor Reentrancy ID HTTP header was still being sent to Actor HTTP servers.
The DotNet SDK uses the existence of this HTTP header in logic to determine what state should be returned to the Actor.
Solution
Don't send the Actor Reentrancy ID HTTP header (
"Dapr-Reentrancy-Id") when Reentrancy is disabled.v1.15.0: Dapr Runtime v1.15.0Compare Source
Dapr 1.15
We're excited to announce the release of Dapr 1.15!
We would like to thank you all for your patience and also give our thanks to all the new and existing contributors who helped make this release happen.
If you're new to Dapr, visit the getting started page and familiarize yourself with Dapr.
Docs have been updated with all the new features and changes of this release. To get started with new capabilities introduced in this release, go to the Concepts and the Developing applications.
Please read the Breaking Changes carefully. If you're experiencing any issues, please report them on Discord. The following core maintainers are available to help you:
@joshvanl, @​yaron2, @​cassie1coyle.See this section on upgrading Dapr to version 1.15.
Acknowledgements
Thanks to everyone who made this release possible!
@adrianhr91, @alicejgibbons, @antontroshin, @aqeelat, @arslanmusta, @artur-ciocanu, @arturotrenard, @artursouza, @bhagya05, @cicoyle, @daixiang0, @diegodocs, @divzi-p, @Druid-of-Luhn, @elena-kolevska, @emsearcy, @evhen14, @famarting, @filintod, @GowthamHN, @hhunter-ms, @humandigital-ruud, @ItalyPaleAle, @Jeroen-VdB, @jev-e, @JoshVanL, @jseguillon, @LeonMatthesKDAB, @lor1113, @luigirende, @m3nax, @marcduiker, @mikeee, @MregXN, @msfussell, @olitomlinson, @passuied, @paule96, @paulyuk, @qustavo, @RafaelJCamara, @rochabr, @salaboy, @shubham1172, @Shubhdeep02, @sicoyle, @siri-varma, @SpiffyEight77, @Taction, @ThomasVitale, @tomhreb, @vil02, @WhitWaldo, @yaron2, @ytimocin, @znd4
Special thanks go to Rob J - You know who you are!
Highlights
These are the v1.15 release highlights:
Dapr Workflow (stable)
Dapr workflow makes it easy to write long running stateful applications using durable execution. You can try out Dapr workflow with the Quickstart Samples. The ability to author and run workflows is now stable. This includes the Dapr runtime along with the Dapr .NET, Java, Python, Go and Javascript SDKs.
The workflow runtime engine has undergone a major overwrite to achieve substantial performance and scalability improvements, as well as reliability and stability traits that are required to run mission critical apps at massive scale. Workflows now support dynamically scaling your Workflow applications from 0 to many replicas, whilst maintaining durability of your tasks at runtime.
Dapr Actors
The Actor runtime engine has had a rewrite in its implementation. Although no changes have been made to the API surface of Actors, this overhaul significantly improves the reliability of handling Actors at scale and in dynamically scaling environments. This work has also been instrumental in making the, now stable, Workflows engine dynamic and durable.
The Actor runtime implementation is now capable of being extended upon to implement new highly requested Actor APIs, or even targeting new Actor targets beyond your app and Workflows in future.
Scheduler Service (stable)
The Scheduler service is the control plane service used to schedule jobs, running in self-hosted mode or on Kubernetes. It is installed when using the Dapr CLI and is the service responsible for managing scheduled jobs. The Scheduler service is now stable
SchedulerRemindersfeature flag is set to true, and all new actor reminders you create are run using the Scheduler service. When you deploy Dapr v1.15, any existing actor reminders are migrated from the Placement service to the Scheduler service as a one time operation for each actor type. You can prevent this migration by setting theSchedulerRemindersflag tofalsein the application configuration file for the actor type. See Scheduler Actor RemindersConversation API (alpha)
A new Conversation API (alpha) reduces the complexity of interacting with large language models (LLM) at scale, providing a consistent API to talk to LLM providers. With the Conversation API, you can:
The Go, .NET, and Rust SDKs have the conversation API implemented as part of this release. As with all APIs, Dapr provides observability by issuing metrics for your LLM interactions.
Learn more about the Conversation API, or dive into a .NET or Go Quickstart.
SDK Improvements
.NET SDK
The .NET SDK added support for the Jobs, Conversation and streaming pub/sub APIs.
Python SDK
The Python SDK added support for streaming pub/sub APIs and the Conversation API.
wait_for_orchestration_startandwait_for_orchestration_completionwas changed from 60 seconds to no timeoutJava SDK
The Java SDK added a Spring Boot integration, including Spring Boot Starters for interacting with the Dapr APIs and testing capabilities using Testcontainers. The Spring Boot integration now supports:
Javascript SDK
The JavaScript SDK added support for the Pause, Resume and SetStatus methods on the Workflow API. Progress is being made to improve the JavaScript SDK documentation.
Go SDK
Rust SDK (alpha)
The Rust SDK added support for the Conversation API support. Progress is being made in other areas towards a refactor for beta/stable state.
CLI and Env Vars
containerImagePullPolicyon KubernetesComponents
New components
The following new components have been added
Component improvements
receiverQueueSizeaddedKubernetes improvements
ClusterRolenew rule granting read-only access tonamespacesresources allowing["get", "list", "watch"]operations.List of issues in this release
Dapr Runtime
securityContext/runAsGroupandsecurityContext/runAsUseras sidecar injector options. 7958app.kubernetes.io/managed-by8052dapr_placement_statefulset.yamlmanifests 8205dapr_placement_leader_statusanddapr_placement_raft_leader_status)8245Dapr CLI
Components
key_sharedfunctionality. 3601.NET SDK
DaprConfigurationStoreProvidernot applying case-insensitive configuration updates correctly. 934GetJobAsyncdeserialization issue 1461Go SDK
Java SDK
Configuration
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