Is it possible to learn about TSDB in Prometheus?
Though Prometheus 2.0 was launched about 3 years ago, there are not much resources to understand it's TSDB other than Fabian's blog post, which is very high level, and the docs on formats is more like a developer reference.
Do I need to evaluate the performance of a TSDB system?
Careful evaluation is required for these systems as they vary greatly in durability, performance, and efficiency. For further details on file format, see TSDB format. The initial two-hour blocks are eventually compacted into longer blocks in the background.
What is the time series database in Prometheus?
Prometheus includes a local on-disk time series database, but also optionally integrates with remote storage systems. Prometheus's local time series database stores data in a custom, highly efficient format on local storage. Ingested samples are grouped into blocks of two hours.
What happens when TSDB has to restart?
In case the TSDB has to restart (gracefully or abruptly), it uses the on-disk memory-mapped chunks and the WAL to replay back the data and events and recontruct the in-memory index and chunk. tsdb/db.go coordinates the overall functioning of the TSDB.
What is compaction in Prometheus?
Compaction consists of writing a new block from one or more existing blocks (called the source blocks or parent blocks), and at the end, the source blocks are deleted and the new compacted block is used in place of those source blocks.
How does Prometheus know to scrape?
Prometheus gathers metrics from different systems by scraping data from HTTP endpoints. It uses this information to identify issues, such as when an endpoint is missing or should not exist or when a time-series pattern indicates a problem.
What is downsampling Prometheus?
Downsampling is the ability to reduce the rate of a signal. As a result, the resolution of the data is reduced and also its size. The main reasons why this is done are cost and performance. Storing the data becomes cheaper and querying the data is faster as the size of the data decreases.
Where does Prometheus store metrics?
As you can check the Prometheus Dockerfile on Github (https://github.com/prometheus/prometheus/blob/master/Dockerfile#L24), the working directory is /prometheus and that where you will find all the metrics and data.
What is Relabel_configs in Prometheus?
Prometheus needs to know what to scrape, and that's where service discovery and relabel_configs come in. Relabel configs allow you to select which targets you want scraped, and what the target labels will be. So if you want to say scrape this type of machine but not that one, use relabel_configs .
What is metrics in Prometheus?
Metrics are a core concept of Prometheus. Instrumented systems expose them, Prometheus stores them in its time-series database and makes them available to easily query to understand how these systems behave over time. In short, a metric is an identifier linking data points together over time.
What is Thanos compact?
The thanos compact command applies the compaction procedure of the Prometheus 2.0 storage engine to block data stored in object storage. It is generally not semantically concurrency safe and must be deployed as a singleton against a bucket. Compactor is also responsible for downsampling of data.
What is Prometheus Sharding?
This is where Prometheus' sharding feature comes into play. It divides the targets Prometheus scrapes into multiple groups, small enough for a single Prometheus instance to scrape. If possible functional sharding is recommended.
What is Thanos querier?
The thanos query command (also known as “Querier”) implements the Prometheus HTTP v1 API to query data in a Thanos cluster via PromQL. In short, it gathers the data needed to evaluate the query from underlying StoreAPIs, evaluates the query and returns the result. Querier is fully stateless and horizontally scalable.
What are metrics used for?
Key Takeaways Metrics are measures of quantitative assessment commonly used for comparing, and tracking performance or production. Metrics can be used in a variety of scenarios. Metrics are heavily relied on in the financial analysis of companies by both internal managers and external stakeholders.
What is open telemetry?
OpenTelemetry is a vendor-neutral standard way to collect telemetry data for applications, their supporting infrastructures, and services. It's now promoted to a Cloud Native Computing Foundation incubating project since its inception in May 2019 with the merger of OpenCensus and OpenTracing projects.
What metrics does Prometheus collect by default?
Prometheus collects metrics from targets by scraping metrics HTTP endpoints. Since Prometheus exposes data in the same manner about itself, it can also scrape and monitor its own health. For a complete specification of configuration options, see the configuration documentation.
What does scraping mean in Prometheus?
In Prometheus terms, an endpoint you can scrape is called an instance, usually corresponding to a single process. A collection of instances with the same purpose, a process replicated for scalability or reliability for example, is called a job.
How often does Prometheus scrape?
every 15 secondsIn this case the global setting is to scrape every 15 seconds. The evaluation_interval option controls how often Prometheus will evaluate rules. Prometheus uses rules to create new time series and to generate alerts. The rule_files block specifies the location of any rules we want the Prometheus server to load.
How does Prometheus work?
Prometheus scrapes metrics from instrumented jobs, either directly or via an intermediary push gateway for short-lived jobs. It stores all scraped samples locally and runs rules over this data to either aggregate and record new time series from existing data or generate alerts.
How does Prometheus work in Kubernetes?
Prometheus uses Kubernetes APIs to read all the available metrics from Nodes, Pods, Deployments, etc. For this reason, we need to create an RBAC policy with read access to required API groups and bind the policy to the monitoring namespace.
How does Prometheus work?
Prometheus integrates with remote storage systems in three ways: Prometheus can write samples that it ingests to a remote URL in a standardized format. Prometheus can receive samples from other Prometheus servers in a standardized format. Prometheus can read (back) sample data from a remote URL in a standardized format.
How many log files does Prometheus have?
Prometheus will retain a minimum of three write-ahead log files. High-traffic servers may retain more than three WAL files in order to to keep at least two hours of raw data.
Does Prometheus have local storage?
Prometheus's local storage is limited to a single node's scalability and durability. Instead of trying to solve clustered storage in Prometheus itself, Prometheus offers a set of interfaces that allow integrating with remote storage systems.
Does Prometheus have a time series?
Prometheus includes a local on-disk time series database, but also optionally integrates with remote storage systems.
Is it safe to backfill Prometheus?
However, they should be careful and note that it is not safe to backfill data from the last 3 hours (the current head block) as this time range may overlap with the current head block Prometheus is still mutating. Backfilling will create new TSDB blocks, each containing two hours of metrics data.
Introduction#
- Though Prometheus 2.0 was launched about 3 years ago, there are not much resources to understand it's TSDB other than Fabian's blog post, which is very high level, and the docs on formatsis more like a developer reference. The Prometheus' TSDB has been attracting lots of new contributors lately and understanding it has been one of the pain points due to lack of resources…
Prologue#
- Fabian's blog post is a good read to understand the data model, core concepts, and the high level picture of how the TSDB is designed. He also gave a talk at PromCon 2017on this. I recommend reading the blog post or watching the talk before you dive into this one to set a good base. All of what I explain in this blog post about the lifecycle of a sample in Head is also explained in my Ku…
Small Overview of Tsdb#
- In the figure above, the Head block is the in-memory part of the database and the grey blocks are persistent blocks on disk which are immutable. We have a Write-Ahead-Log (WAL) for durable writes. An incoming sample (the pink box) first goes into the Head block and stays into the memory for a while, which is then flushed to the disk and memory-mapp...
Life of A Sample in The Head#
- All the discussions here are about a single time seriesand the same applies to all the series. The samples are stored in compressed units called a "chunk". When a sample is incoming, it is ingested into the "active chunk" (the red block). It is the only unit where we can actively write data. While committing the sample into the chunk, we also record it in the Write-Ahead-Log (WAL) on …
Few More Things to Note/Understand#
- Where is the index?#
It is in the memory and stored as an inverted index. More about the overall idea of this index is in Fabian's blog post. When the compaction of Head block occurs creating a persistent block, Head block is truncated to remove old chunks and garbage collection is done on this index to remove … - Handling Restarts#
In case the TSDB has to restart (gracefully or abruptly), it uses the on-disk memory-mapped chunks and the WAL to replay back the data and events and recontruct the in-memory index and chunk.
Code Reference#
- tsdb/db.gocoordinates the overall functioning of the TSDB. For the parts relevant in the blog post, the core logic of ingestion for the in-memory chunks is all in tsdb/head.gowhich uses WAL and memory mapping as a black box.
More Blog Posts to Expect in The Future on Tsdb#
- WAL and its checkpointing. (Prometheus TSDB (Part 2): WAL and Checkpoint)
- Memory-mapping of in-memory chunks from the disk. (Prometheus TSDB (Part 3): Memory Mapping of Head Chunks from Disk)
- Persistent blocks along with its index. (Prometheus TSDB (Part 4): Persistent Block and its Index)
- WAL and its checkpointing. (Prometheus TSDB (Part 2): WAL and Checkpoint)
- Memory-mapping of in-memory chunks from the disk. (Prometheus TSDB (Part 3): Memory Mapping of Head Chunks from Disk)
- Persistent blocks along with its index. (Prometheus TSDB (Part 4): Persistent Block and its Index)
- Queries in TSDB. (Prometheus TSDB (Part 5): Queries)
