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Runner Integration

Non goals

This proposal does not address deployment of the Step Runner binary into target environments, nor of starting the Step Runner gRPC service described below. The rest of the proposal assumes both that the Step Runner binary exists in the target environment and that the gRPC service is running and listening on a local socket. Similarly this proposal does not address the life-cycle of the Step Runner service, and how to handle things like restarting the service if it dies, or upgrades.

See Deployment and Lifecycle Management for relevant blueprint.

Steps Service gRPC Definition

The Step Runner service gRPC definition is as follows:

service StepRunner {
    rpc Run(RunRequest) returns (RunResponse);
    rpc FollowSteps(FollowStepsRequest) returns (stream FollowStepsResponse);
    rpc FollowLogs(FollowLogsRequest) returns (stream FollowLogsResponse);
    rpc Finish(FinishRequest) returns (FinishResponse);
    rpc Status(StatusRequest) returns (StatusResponse);

message Variable {
    string key = 1;
    string value = 2;
    bool file = 3;
    bool masked = 4;

message Job {
    repeated Variable variables = 1;
    string job_id = 2;
    string pipeline_id = 3;
    string build_dir = 4;
    repeated string token_prefixes = 5;

message Masking {
    repeated string phrases = 1;
    repeated string token_prefixes = 2;

message RunRequest {
    string id = 1;
    string work_dir = 2;
    map<string,string> env = 3;
    Masking masking = 4;
    Job job = 5;
    string steps = 6;

message RunResponse {

message FollowStepsRequest {
    string id = 1;

message FollowStepsResponse {
    StepResult result = 1;

message FollowLogsRequest {
    string id = 1;
    int32 offset = 2;

message FollowLogsResponse {
    bytes data = 1;

message FinishRequest {
    string id = 1;

message FinishResponse {

message Status {
    string id = 1;
    bool finished = 2;
    int32 exit_code = 3;
    google.protobuf.Timestamp start_time = 4;
    google.protobuf.Timestamp end_time = 5;

message StatusRequest {
    string id = 1;

message StatusResponse {
    repeated Status jobs = 1;

Runner interacts with Step Runner over the above gRPC service which is started on a local socket in the execution environment. Runner accesses the local socket by first connecting to the target environment via executor-specific protocols, then use a provided proxy command to connect to the gRPC service, and transparently tunnel gRPC requests from the Runner to Step Runner (seeProxy Command). This is the same way that Nesting serves a gRPC service in a dedicated Mac instance. The service has five RPCs, Run, FollowSteps, FollowLogs, Finish and Status.

Run is the initial delivery of the steps. FollowSteps requests a streaming response of step-result traces. FollowLogs similarly requests a streaming response of output (stdout/stderr) written by processes executed as part of running the steps, and logs produced by Step Runner itself. Finish stops execution of the request (if still running) and cleans up resources as soon as possible. Status lists the status of the specified job, or if no job was specified, of all active jobs in the Step Runner service (including completed but not Finished jobs). Status can for example be used by a runner to recover after a crash.

The Step Runner gRPC service will be able to execute multiple Run payloads at once. That is, each call to Run will start a new goroutine and execute the steps until completion. Multiple calls to Run may be made simultaneously.

As steps are executed, step-result traces and sub-process logs can be streamed back to GitLab Runner. This allows Runner (or any caller) to follow execution, at the step level for step-result traces (FollowSteps), and as written for sub-process and Step Runner logs (FollowLogs). Logs will be written in a specific format, and sensitive tokens will be masked by Step Runner before being streamed to Runner.

All APIs excluding Status are idempotent, meaning that multiple calls to the same API with the same parameters should return the same result. For example, If Run is called multiple times with the same id, only the first invocation should begin processing of the job request, and subsequent invocations return a success status but otherwise do noting. Similarly, multiple calls to Finish with the same id should finish and remove the relevant job on the first call, and do nothing on subsequent calls.

The service should not assume clients will be well-behaved, and should be able to handle clients that never call or prematurely disconnect from either of the Follow APIs, and also clients that never call Finish on a corresponding Run request. To this end the Step Runner process should periodically perform a scan to identify and prune stale or runaway/stuck jobs. A stale job could be a job that has finished some specified time ago (and has not been Finished). A runaway job is a job that has been running some (long) specified amount of time, possibly without producing output.

Finally, to facilitate integrating steps into the below runner executors, it is recommended that steps provide a client library to coordinate execution of the Run/Follow*/Finish APIs, and to handle reconnecting to the step-runner service in the event that the Follow* calls loose connectivity.

RunRequest Parameters

Steps are delivered to Step Runner in the RunRequest.Steps field as a JSON-serialized version of step.go, with no processing of the step definition required by runner itself. The id field uniquely identifies each request running on the Step Runner service. The RunRequest.Env field holds environment variable that are to be injected into the environment when each step is executed.

The optional Job parameter will include select parameters from the corresponding CI job. Job will include the corresponding CI job’s build directory; Job.BuildDir should be copied to RunRequest.WorkDir, and all steps in a request should be invoked in that directory to preserve existing job script behavior. The RunRequest will also include the CI job’s environment variables (i.e. the variables defined at the job and global levels in the CI configuration). When a RunRequest is made by Runner, variables must be included in Job.Variables, and RunRequest.Env should be left empty. When the run request is processed, file-type variables will be written to file, variables will be expanded, copied into RunRequest.Env, and the Job field will be discarded from the remainder of the request. Variables should be expanded by the Step Runner service since they may reference object in the execution environment (like other environment variables or paths). This includes file-type variables, which should be written to the same path as they are be in traditional runner job execution. Similarly, from Job.Variables, phrases to be masked should be extracted and used to populate Masking.Phrases, and Job.TokenPrefixes should be copied into Masking.TokenPrefixes.

Clients other than Runner wishing to run steps can omit the Job field, and in this case the Masking and Env fields should be populated directly by the caller.

Log Format

Log lines emitted buy the FollowLogs API should have the format

    <timestamp> <stream> <stdout/stderr> <append flag> <message>

This is the same log format introduce into runner in this merge request. The logging library used to produce this format should be shared between GitLab Runner and Step Runner.


Step Runner will be responsible for masking sensitive variables or tokens. This should be done before the raw log message is formatted into the above log format. The libraries used to mask variables should shared between GitLab Runner and Step Runner. (See relevant modules).

Proxy Command

The Step Runner binary will include a command to proxy data from (typically text-based) stdin/stdout/stderr-based protocols to the gRPC service. This command will run in the same host as the gRPC service, and will read input from stdin, forward it to the gRPC service over a local socket, receive output from the gRPC service over same socket, and forward it to the client via stdout/stderr. This command will enable clients (like Runner) to transparently tunnel to the gRPC service via stdin/stderr/stdout-based protocols like SSH or docker exec, which will eliminate the need to expose the Step Runner service’s gRPC port on Docker images, or set up SSH port forwarding on VMs, and will allow runner to interact with Step Runner using established protocols (i.e. SSH and docker exec). stdout should be reserved for writing responses from the Step Runner service, and stderr should be reserved for errors originating in the proxy command itself.


Here is how GitLab Runner will connect to Step Runner in each runner executor:


The Instance executor is accessed via SSH, the same as today. However instead of starting a bash shell and piping in commands, it invokes the proxy command, which in turn connects to the Step Runner socket in a known location. Runner can then make gRPC calls directly, and transparently tunnel through the SSH connection to the gRPC service. This is the same as how Runner calls the Nesting server in dedicated Mac instances to make VMs.

This requires that Step Runner is present and started in the job execution environment.


The same requirement that Step Runner is present and the gRPC service is running is true for the Docker executor (and docker-autoscaler). However in order to connect to the gRPC service inside the container, Runner will docker exec to the container and execute the proxy command to connect to the gRPC service in the container. The client can then write to the docker exec’s stdin, which will transparently be proxied to the gRPC service, and read from its stdout/stderr, which will contain responses from the gRPC service.


The Kubelet on Kubernetes Nodes exposes an exec API which will start a process in a container of a running Pod. We will use this to exec create a bridge process that will allow the caller to make gRPC calls inside the Pod, similar to the Docker executor.

In order to access to this protected Kubelet API we must use the Kubernetes API which provides an exec sub-resource on Pod. A caller can POST to the URL of a pod suffixed with /exec and then negotiate the connection up to a SPDY protocol for bidirectional byte streaming. So GitLab Runner can use the Kubernetes API to connect to the Step Runner service and deliver job payloads.

This is the same way that kubectl exec works. In fact most of the internals such as SPDY negotiation are provided as client-go libraries. So Runner can call the Kubernetes API directly by importing the necessary libraries rather than shelling out to Kubectl.

Historically one of the weaknesses of the Kubernetes Executor was running a whole job through a single exec. To mitigate this Runner uses the attach command instead, which can “re-attach” to an existing shell process and pick up where it left off.

This is not necessary for Step Runner however, because the exec is just establishing a bridge to the long-running gRPC process. If the connection drops, Runner will just “re-attach” by exec’ing another connection and continuing to make RPC calls like follow.