Security infrastructure playbooks

Contains playbooks for GCP project deployments, GKE project deployments,

GKE deployment playbooks

This section contains playbooks for how to deploy our k8s infrastructure


How to deploy and update logging k8s deployments.

Deploy pubsubbeats

This deploys pubsubbeats. Currently this will deploy it to production, but these documents will be updated to reflect environment-specific deployments in #17281. Note that this will update an existing k8s deployment if one already exists.

  1. Install helmfile
  2. Get access to the logging cluster by running gcloud container clusters get-credentials --region us-central1-f --project sourcegraph-security-logging logging
  3. From security/logging/helm/pubsubbeat run the command helmfile template | kubectl --context gke_sourcegraph-security-logging_us-central1-f_logging apply -f -

Logging staging

To implement in #17281.

GCP deployment playbooks

Playbooks and step-by-step instructions on how to deploy our projects. It’s assumed that you already have terraform installed.

It’s recommended that you use tfenv to help manage terraform versions.

For basic terraform issues, see debugging terraform

Creating a new GCP project

This is done via terraform from gcp/projects in the Sourcegraph infrastructure repository. Unless you’re a GCP admin, you’ll be blocked on permissions here.

  1. Update the security_projects collection to include a new project.
    1. The fields name, billing_account, and services must be set.
    2. The name of the object should be the same as the name field.
    3. billing_account should always be set to "default".
    4. services is a list of non-default APIs required by the project.
  2. At this point, you will very likely be blocked on IAM Permissions. If you’re not, then… Hi Bill Creager, hope you’re well today!
  3. To verify that your change is correct, run terraform plan from gcp/projects in our infrastructure repository.
  4. If the change is purely additive, you’re free to apply it by running terraform apply and entering yes at the prompt. If anything is updated or deleted, check with the project owner to see what’s out of sync, and whether it’s ok to still apply the change.
  5. Assuming terraform apply succeeds, update the security infrastructure page and the environments page of the handbook to reflect the new project.
  6. Create an empty folder under security in the infrastructure repository to store future terraform configuration.

Deploying logging infrastructure

These should be one-offs. Never do this unless the project is irretrievably broken, or we need a new copy somewhere.

Staging infrastructure

To implement in #17281.

Production infrastructure

This requires multiple steps to properly configure. Most of these are going to be conditional on changing things that aren’t expected to change. Usually you’ll want deploy pubsubbeats

From scratch
  1. Configure the sourcegraph-security-logging project by running terraform apply from /security/logging.
  2. Configure the pub/sub logging sinks, as well as GKE workload audit logs in cloud and dogfood by running terraform apply from /cloud and /dogfood
    1. This would only be needed on config changes for the logging sinks or the audit log module.
  3. Create a service account key for the subscriber in the sourcegraph-security-logging project.
  4. Create our elastic instance.
    1. Note that the following instructions are part of creating the Elastic instance, since pubsubbeats perform some Elastic configuration
  5. Encrypt elastic secrets and add them to the repository.
  6. Deploy pubsubbeats.

Encrypt deployment secrets

This should never need to happen after initial cluster creation.

Currently only documented for production logging, but these documents will be updated to reflect environment-specific deployments in #17281.

This assumes that you have the json-formatted service account key for the pubsubbeat-subscriberservice account, the username & password for the elastic pubsubbeat user, and the elastic cloud ID on hand.

Pipe a file of format:

CLOUD_ID: "[cloud_id]"
CLOUD_AUTH: "[pubsubbeat_username]:[pubsubbeat_password]"

Note that the format of CREDENTIALS_PUBSUB needs to have the opening { indented, but does not need the closing } indented.

	"Foo": "Bar",
	"Alpha": "Beta"

Into the command gcloud --project sourcegraph-security-logging kms encrypt --location us-central1 --keyring=encryption-keyring --key helm-secrets --ciphertext-file=- --plaintext-file=-, and store the output in security/logging/helm/pubsubbeat/private/pubsubbeat_secrets.yaml.enc

Ingesting logs from a new GCP project

From the project directory in the infrastructure repository, create the file with the following default configuration. This lets all relevant logs through.

# Sends all logs with a severity of >= default to the security topic
resource "google_logging_project_sink" "security_logging_sink" {
  name        = "log-sink"
  destination = "${var.security_logging_topic_id}"
  # Ingest any log of level default or above
  # We need to ingest default logs, since that's the level of our audit logs
  filter = "severity >= DEFAULT"

  unique_writer_identity = true

Add an entry to

variable "security_logging_topic_id" {
  description = "security logging topic id"

Add an entry to terraform.tfvars

security_logging_topic_id = "[SECURITY_TOPIC_ID]"

Note that the production topic ID is "projects/sourcegraph-security-logging/topics/logs"

Add an entry to

output "security_logging_sink_writer_id" {
  value       = google_logging_project_sink.security_logging_sink.writer_identity
  description = "Security logging sink writer ID"

Once you apply the changes, copy down the logging sink writer ID. Now, the project has been configured to send its logs to the security logging topic. However, it needs to be granted permission to write to this topic. To do this, go to security/logging, and make the following changes.

Add an entry to

# Grant the IAM account used by the [PROJECT_NAME] logging sink permissions to write to the pubsub topic
resource "google_pubsub_topic_iam_member" "sink_permission_[PROJECT_NAME]" {
  topic  =
  role   = "roles/pubsub.publisher"
  member = var.[PROJECT_NAME]_project_writer_identity

Add an entry to

variable "[PROJECT_NAME]_project_writer_identity" {
  description = "writer identity from [PROJECT_NAME] sink"

Add an entry to terraform.tfvars

[PROJECT_NAME]_project_writer_identity  = "[SINK_WRITER_ID]"

Apply the changes via terraform plan and terraform apply.

Validate that the logs are being ingested into elastic by searching json.resource.labels.project_id :[PROJECT_ID] in Kibana. Give it a minute or two to propagate the changes.

Ingesting audit logs from a new GKE cluster

This assumes that stackdriver logs are already ingested by pubsubbeats. If not, do this first.

All of this is done from the project directory in the infrastructure repository.

Note: if any of these objects already exist, make sure the specified fields are a superset of the fields defined here. If the provided fields are not a superset of the fields specified here, add fields until it contains a superset of the fields defined in this document.

Create the file

module "gke_logging" {
  source = "[PATH_TO_MODULES]/modules/gke-logging/"

  # Explicitly pass down the configured k8s provider
  providers = {
    kubernetes = kubernetes

Add an entry to This is what is used to authenticate to the cluster.

# Query the client configuration for our current service account, which should
# have permission to talk to the GKE cluster.
data "google_client_config" "current" {}

Add an entry to If a kubernetes provider already exists, add any missing configuration until this configuration is a subset of the existing kubernetes provider.

# Declare the k8s provider used by the gke-logging module
# Authenticate to the relevant cluster
provider "kubernetes" {
  load_config_file = false
  host             = google_container_cluster.[CLUSTER_WE_WANT_LOGS_FROM].endpoint

  cluster_ca_certificate = base64decode(
  token = data.google_client_config.current.access_token

Run terraform plan, then terraform apply if the plan is as expected.

To validate that we succeeded, run kubectl get pods -n cos-auditd and verify that there is one pod per node. Additionally, go to the log explorer and search for logs with the query jsonPayload._AUDIT_FIELD_A0: *.

Managed service deployment playbooks

Playbooks for deploying and configuring our managed services.

Scaling elastic cloud

Assuming Elastic Cloud is in Healthy state, or in Warn state because it hasn’t had a snapshot in a few hours, scaling Elastic should be trivial. To scale Elastic, follow these instructions to edit the deployment, and increase the number of nodes. If Elastic is already out of disk, and in red state, follow the instructions in Debugging Elastic

Elastic cloud logging

How to configure a production-ready Elastic Cloud deployment for pubsubbeats logging.

  1. Create an Elastic deployment

    1. This should never happen unless the entire project is re-created.

    2. Basic Configuration: Elastic stack I/O optimized AWS cloud provider on US East

    3. Open advanced configuration before creating the deployment 6*58GB nodes for Elasticsearch, 2 zones. 4GB master node 4GB Kibana node

    4. Open security configuration in Kibana Click launch kibana then click manage on the main page. Then click Roles on the sidebar

      Create two roles. pubsubbeat_setup with the cluster privileges monitor, manage_ilm, manage_ml

      pubsubbeat_writer with the cluster privileges cluster:admin/ingest/pipeline/get, monitor and give it index privileges all on indicies pubsubbeat* Create a user pubsubbeat. Give it the roles pubsubbeat_setup and pubsubbeat_writer Give it a secure password, and keep track of this value.

  2. Update and re-encrypt the secret values stored in security/logging/helm/pubsubbeat/private/pubsubbeat_secrets.yaml.enc. See these instructions

  3. Deploy pubsubbeats

    1. This allows pubsubbeats to perform the majority of the initial Elasticsearch configuration.
  4. Add additional index configuration

    1. Configure the Kibana index (Pubsubbeats will create this index)

      1. Open index management in Kibana Update the pubsubbeat index template Update the lifecycle field to contain "refresh_interval": "30s"

        lifecycle {
        	"refresh_interval": "30s"
    2. Configure the index lifecycle policy pubsubbeat

      1. Update the maximum index size to be 50 GB.

Debugging playbooks

Playbooks for debugging GCP projects, GKE projects, and managed services.

Debugging logging

If no pubsubbeat logs are are being sent to Elastic logging/helm/pubsubbeat/charts/pubsubbeat/templates/deployment.yaml to run with arguments args: ["-c", "/usr/local/bin/pubsubbeat -c /etc/configmap/pubsubbeat.yml -e -d \"*\"]. This enables debug logging. Then, search through the output logs for connection error, and other things that might indicate why the logs aren’t reaching Elastic. Also check to see that Elastic disk usage is below ~80% in at least two different nodes. If it’s not, scale Elastic immediately.

If some pubsubbeat logs aren’t being sent to elastic, try to find the logs in the gcp logs explorer. Note that you should look in the project generating the logs, not the security project. If they’re not there, then you need to determine why they’re not being ingested by stackdriver. Otherwise, verify that the logging sink is properly configured for that project, and that it’s not filtering out the logs you’re expecting.

Debugging logging stage

To implement in #17281.

Debugging elastic

Note that Elastic will often be in Warn state since we create snapshots on a daily basis, not an hourly basis, since each snapshot takes an hour or two to create. This is intentional, and we should only be concerned if the last snapshot was more than ~26 hrs ago.

While Elastic shouldn’t need too much debugging, occasionally it can get itself stuck into bad states when running out of disk, or when its resources are overloaded. A good utility to manage Elastic is cerebro, which can easily be run via docker. You’ll want to have an Elastic superuser for this, which can be created by a similar process as used in elastic cloud configuration step 1.4.

If you run out of disk space and can’t scale the cluster because shards aren’t getting scheduled due to each node hitting the low or high watermarks

  1. Set cluster.routing.allocation.disk.watermark.low to 92% and cluster.routing.allocation.disk.watermark.high to 94%.
  2. Scale the cluster immediately in extended maintenance mode. In this condition, it’s also fine to skip making a new snapshot, since the cluster is in an extremely unhealthy status anyways.
  3. Once scaling succeeds, set cluster.routing.allocation.disk.watermark.low back to 85% and cluster.routing.allocation.disk.watermark.high back to 90%.

If Elastic runs out of disk, the alias may be deleted, which leads to pubsubbeat being unable to write to Elastic. A workaround is identified in this GitHub issue. These commands can be run from the API console.

Debugging terraform

Basic Terraform errors that are common to run into. See terraform playbooks for uncommon terraform issues.

If you get the error Unsupported Terraform Core version [...] required_version = "A.B.C", or the error Error: Error loading state: state snapshot was created by Terraform vA.B.C, which is newer than current vX.Y.Z; upgrade to Terraform vA.B.C or greater to work with this state, that means you need to use the specific terraform version A.B.C. An easy solution is to run tfenv use A.B.C.

  1. If you get the error No installed versions of terraform matched 'A.B.C , then you need to install A.B.C. To do this, run tfenv install A.B.C before running tfenv use A.B.C.

You may need to run terraform init if you’ve added a new plugin to your configuration, or if you haven’t run terraform commands from this directory before.

If terraform plan results in more changes than expected, try merging in the most recent main branch.

  1. If this still shows unexpected changes, try running terraform plan from the main branch. If the unexpected changes are gone, then it’s an issue with your PR. However, if the unexpected delta is still present from the main branch, it could mean one of a few things.
    1. Someone has an approved PR and is applying some changes before merging. Check in #distributioneers or the PRs on the infrastructure repository.
    2. GCP has updated how things are configured. This is somewhat common with large projects like dogfood and cloud. This is usually means that GCP switched the default “true” value of a field (ex. "on" ->"true"). This results in terraform detecting a change between the local and remote state, despite there not actually being one. This is annoying and confusing, but usually harmless. Usually not something we’d need to deal with, since we don’t have large projects, but this often occurs when modifying dogfood or dotcom. Go bug the owner of the project, or verify that GCP did make an unexpected change.

If terraform plan or terraform apply fails on acquiring state lock, look at the who field of the error.

  • If the who field is obviously a developer, they’re probably also running terraform plan or terraform apply on the same GCP resources. You’ll probably have a merge conflict at some point, so it’s a good idea to sync with them on what the two of you are doing, and how it could interact.
  • If the who field is buildkite, then we may have a stuck pipeline. A good heuristic is to see if the lock was created more than ~10 minutes ago. If it was, it’s a good idea to start hunting through PRs on the infrastructure repo for a stuck pipeline so you can ping the PR author, or to ping #distributrioneers if you can’t find the source. You may need to force unlock the state after killing the stuck pipeline.