Adding New Stacks

Introduction

What are Stacks? Start here: https://tembo.io/blog/tembo-stacks-intro. Stacks are “blueprints” for deploying PostgreSQL, extensions, tools, configurations, and anything else related to making a database fit a specific use case better. The generic Stack specification lives in code and is enforced by a Rust Struct. The Stack Spec defines everything that should be created or configured for a given Tembo instance. All Stacks are defined in YAML. See the stack spec files in the tembo repo for current examples of all existing Stacks. To build a new Stack, you must define it in YAML.

Prerequisite knowledge

Building the Stack definition

The best way to start building a new stack is to start with an existing Stack definition.

Copy the existing stack into a new file, e.g. my_stack.yaml.

Then, go through each attribute and update it such that it fulfills the requirements of your Stack.

Choose a name

Stack names must be globally unique within Tembo.

name: MyStack

Specify container image

Tembo supports stacks based on the current PostgreSQL version and two trailing ones. At the time of writing, this means PostgreSQL 16, 15, and 14, which are configured like so:

repository: "quay.io/tembo"
images:
  14: "standard-cnpg:14-ed6e9e9"
  15: "standard-cnpg:15-ed6e9e9"
  16: "standard-cnpg:16-ed6e9e9"

Define compute templates

These are recommended CPU/memory combinations for the stack’s workload and influence what options the user will see when instantiating a stack through the Tembo Cloud UI.

compute_templates:
  - cpu: 1
    memory: 4Gi
    instance_class: GeneralPurpose
  - cpu: 2
    memory: 8Gi
    instance_class: GeneralPurpose
  - cpu: 1
    memory: 2Gi
    instance_class: ComputeOptimized
  - cpu: 2
    memory: 4Gi
    instance_class: ComputeOptimized

Extensions

Two sections of configuration affect extension behavior: one specifies which are to be installed to the system itself (using trunk) and the other specifies which are to be created (using CREATE EXTENSION) once the database starts.

Installation

Consulte pgt.dev for the current list of available extensions and versions. Specifying extensions to install after that is relatively straightforward:

trunk_installs:
  - name: pgmq
    version: 1.1.1
  - name: pg_partman
    version: 4.7.4

Creation

Set their version, and which database to create them in.

extensions:
  - name: pgmq
    locations:
      - database: postgres
        enabled: true
        version: 1.1.1
  - name: pg_partman
    locations:
      - database: postgres
        enabled: true
        version: 4.7.4

Set the configuration engine

Tembo’s “PostgreSQL Configuration Engines” are designed to dynamically calculate and set certain PostgreSQL configuration values based on:

  • system infrastructure values such as CPU, memory, storage
  • other PostgreSQL config values, e.g. “half of max_connections”

For example, an engine could derive work_mem based on number of connections, and shared_buffers based on total memory. See the standard config engine here for details on how it works.

Presently there are only two options:standard and olap

postgres_config_engine: standard

Set static config values

For example, these are postgresql.conf values that are static. They can, however, be overridden by the user. Be sure to include your extensions in the list of shared_preload_libraries if their documentation mentions this requirement.

postgres_config:
  - name: shared_preload_libraries
    value: pg_stat_statements,pg_partman_bgw
  - name: pg_partman_bgw.dbname
    value: postgres
  - name: pg_partman_bgw.interval
    value: 60
  - name: pg_partman_bgw.role
    value: postgres
  - name: random_page_cost
    value: 1.1
  - name: autovacuum_naptime
    value: '20s'
  - name: autovacuum_vacuum_cost_limit
    value: 10000
  - name: autovacuum_vacuum_scale_factor
    value: 0.05
  - name: autovacuum_vacuum_insert_scale_factor
    value: 0.05
  - name: autovacuum_analyze_scale_factor
    value: 0.05
  - name: track_io_timing
    value: 'on'
  - name: checkpoint_timeout
    value: 10min
  - name: pg_stat_statements.track
    value: all

Define containers to run next to PostgreSQL

App Services are containers that deploy alongside the primary PostgreSQL container in a stack. There are few restrictions on the types of things an App Service can do: so long as the container can be found during deployment, it can be deployed in a stack. The AppService spec lives here.

name

The name must be unique per Tembo instance, but is only limited by Kubernetes naming conventions.

image

Container image name. This could be any image available in public container registries such as but not limited to quay.io, Docker Hub, or ghcr.io.

More info: https://kubernetes.io/docs/concepts/containers/images

image: postgrest/postgrest:v10.0.0

command

A list of arguments needed to start the main command within the container. The container image’s ENTRYPOINT is used if this is not provided. Variable references with the syntax $(VAR_NAME) are expanded using the container’s environment. If a variable cannot be resolved, the reference in the input string will be unchanged. Double dollar signs ($$) are reduced to a single $, which allows for escaping the $(VAR_NAME) syntax, i.e. "$$(VAR_NAME)" will produce the string literal "$(VAR_NAME)". Escaped references will never be expanded, regardless of whether the variable exists or not. See the relevant Kubernetes documentation for more detail.

command:
 - python
 - -m
 - run.py

args

Arguments passed to the container’s main command. The container image’s CMD is used if this is not provided. Variable references $(VAR_NAME) are expanded using the container’s environment. Variable interpolation rules are the same as with command.

env

Environment variables to inject into the container. The tembo operator will inject postgres connection strings (read only or a read write connection) into the container if it is configured to do so.

env:
- name: MY_ENV_VAR
  value: "my_value"
- name: VAR_DERIVED_FROM_PLATFORM
  valueFromPlatform: ReadOnlyConnection|ReadWriteConnection

resources

Compute Resources required by this container. See the relevant Kubernetes documentation for more information.

resources:
      requests:
        cpu: 100m
        memory: 256Mi
      limits:
        cpu: 400m
        memory: 256Mi

probes

Configuration which tells kubernetes how to check in on the status of the container, i.e. how to verify that the container has started and is in a state of good health?

probs:
/// Periodic probe of container service readiness. Container will be removed from service endpoints if the probe fails. Cannot be updated. More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
	readiness:
		path: /health/ready
		port: 3000
		initial_delay_seconds: 2
/// Periodic probe of container liveness. Container will be restarted if the probe fails. Cannot be updated. More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
	liveness:
		path: /health/ready
		port: 3000
		initial_delay_seconds: 2

middlewares

Middlewares configure how incoming requests should be mutated before reaching the container specified by this App Service. Middlewares are specific to one Tembo instance. They are defined under this attribute, but used under the routing section of appServices.

Middlewares are enums, meaning there are only specific values or types of middlewares that are supported. Currently those are customRequestHeaders, stripPrefix, and replacePathRegex. See Traefik’s documentation for more information.

middlewares:
  - !customRequestHeaders
      name: headers
      config:
        Authorization: ""
        Content-Profile: pgmq
        Accept-Profile: pgmq
  - !stripPrefix
      name: strip-prefix
      config:
        - /rest/v1
  - !replacePathRegex
      name: map-pgmq
      config:
        regex: \/pgmq\/v1\/?
        replacement: /rpc/

routing

Routing describes how the container should be exposed outside of the Kubernetes cluster.

In the example below, are telling Traefik to match requests on the path “/pgmq/v1” and to route them to port 3000 on the container. Before the requests reach the container, Traefik will apply the map-pgmq, strip-prefix, and headers ”Middlewares” to the request, which are defined in the middlewares section of the appService spec.

routing:
  - port: 3000
    ingressPath: /pgmq/v1
    middlewares:
      - map-pgmq
      - strip-prefix
      - headers

Complete Spec

You will end up with something like this:

name: MessageQueue
description: A Tembo Postgres Stack optimized for Message Queue workloads.
repository: "quay.io/tembo"
image: "standard-cnpg:15.3.0-1-1096aeb"
stack_version: 0.3.0
appServices:
  - name: postgrest
    image: postgrest/postgrest:v10.0.0
    routing:
      - port: 3000
        ingressPath: /pgmq/v1
        middlewares:
          - map-pgmq
          - strip-prefix
          - headers
    middlewares:
      - !customRequestHeaders
          name: headers
          config:
            Authorization: ""
            Content-Profile: pgmq
            Accept-Profile: pgmq
      - !stripPrefix
          name: strip-prefix
          config:
            - /rest/v1
      - !replacePathRegex
          name: map-pgmq
          config:
            regex: \/pgmq\/v1\/?
            replacement: /rpc/
    env:
      - name: PGRST_DB_URI
        valueFromPlatform: ReadWriteConnection
      - name: PGRST_DB_SCHEMA
        value: "public, pgmq"
      - name: PGRST_DB_ANON_ROLE
        value: postgres
      - name: PGRST_LOG_LEVEL
        value: info
compute_templates:
  - cpu: 1
    memory: 4Gi
  - cpu: 2
    memory: 8Gi
  - cpu: 4
    memory: 16Gi
  - cpu: 8
    memory: 32Gi
  - cpu: 16
    memory: 32Gi
trunk_installs:
  - name: pgmq
    version: 0.31.0
  - name: pg_partman
    version: 4.7.3
extensions:
  - name: pgmq
    locations:
      - database: postgres
        enabled: true
        version: 0.31.0
  - name: pg_partman
    locations:
      - database: postgres
        enabled: true
        version: 4.7.3
postgres_metrics:
  pgmq:
      query: select queue_name, queue_length, oldest_msg_age_sec, newest_msg_age_sec, total_messages from pgmq.metrics_all()
      master: true
      metrics:
        - queue_name:
            usage: LABEL
            description: Name of the queue
        - queue_length:
            usage: GAUGE
            description: Number of messages in the queue
        - oldest_msg_age_sec:
            usage: GAUGE
            description: Age of the oldest message in the queue, in seconds.
        - newest_msg_age_sec:
            usage: GAUGE
            description: Age of the newest message in the queue, in seconds.
        - total_messages:
            usage: GAUGE
            description: Total number of messages that have passed into the queue.
postgres_config_engine: standard
postgres_config:
  - name: shared_preload_libraries
    value: pg_stat_statements,pg_partman_bgw
  - name: pg_partman_bgw.dbname
    value: postgres
  - name: pg_partman_bgw.interval
    value: 60
  - name: pg_partman_bgw.role
    value: postgres
  - name: random_page_cost
    value: 1.1
  - name: autovacuum_naptime
    value: '20s'
  - name: autovacuum_vacuum_cost_limit
    value: 10000
  - name: autovacuum_vacuum_scale_factor
    value: 0.05
  - name: autovacuum_vacuum_insert_scale_factor
    value: 0.05
  - name: autovacuum_analyze_scale_factor
    value: 0.05
  - name: track_io_timing
    value: 'on'
  - name: checkpoint_timeout
    value: 10min
  - name: pg_stat_statements.track
    value: all

Running and Testing a Stack

  • Manually translate the Stack template onto the CoreDBSpec resource spec. See yaml/sample-message-queue.yaml for an example of the MQ Stack mapped to a CoreDB resource. Name it my_coredb.yaml or something else that makes sense.
  • Follow the Run Tembo Locally guide to get tembo set up locally.
  • Install your Tembo Stack into the local kubernetes cluster kubectl apply -f </path/to/my_coredb.yaml

Requesting inclusion in Tembo Cloud

Open an issue on the Tembo Github Repo or drop us a line in Slack.

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