Steam download stopping? Update stuck? The Steam disk write error can stop you from installing or updating a game; we've got 13 ways you can. Write Error Rate- the frequency of errors that occur when recording to the hard drive, this indicator usually judges the quality of the surface of the. Write Error Rate (Multi Zone Error Rate) - the frequency of occurrence of errors when writing data. Shows the total number of errors detected during the.
Thematic video🔴كيفية إصلاح الباد سيكتور من خلال الويندوز - Victoria - Repair Bad Sector Cloud Storage & Cloud Backup. Retrieved
Resolving of Pending sectors can be done with mhdd (scan with relocate) and with victoria.
MHDD is the most popular freeware program for low-level IDE, Serial ATA and SCSI HDD diagnostics.
Raw Read Error Rate a critical SMART parameter that indicates problem with the disk surface (platter that stores the data), the actuator arm, and the read/write head. A higher RAW Read Error Rate indicates higher chances of disk failure.
On different drives this parameter works differently. For example on Seagate drives it's quite normal to have high Raw Read Error Rate. On WD drives Raw Read Error Rate should be zero.
VictoriaMetrics is a fast, cost-effective and scalable time series database. It can be used as a long-term remote storage for Prometheus.
It is recommended to use the single-node version instead of the cluster version for ingestion rates lower than a million data points per second. The single-node version scales perfectly with the number of CPU cores, RAM and available storage space, write error rate victoria. The single-node version is easier to configure write error rate victoria operate compared to the cluster version, so think twice before choosing the cluster version. See this question for more details.
Join our Slack or contact us with consulting and support questions.
VictoriaMetrics cluster consists of the following services:
- - stores the raw data and returns the queried data on the given time range for the given label filters
- - accepts the ingested data and spreads it among nodes according to consistent hashing over metric name and all its labels
- - performs incoming queries by fetching the needed data from all the configured nodes
Each service may scale independently and may run on the most suitable hardware. nodes don't know about each other, don't communicate with each other and don't share any data. This is a shared nothing architecture. It increases cluster availability, and simplifies cluster maintenance as well as cluster scaling.
VictoriaMetrics cluster supports multiple isolated tenants (aka namespaces). Tenants are identified by orwhich are put inside request urls. See these docs for details. Some facts about tenants in VictoriaMetrics:
Each and is identified by an arbitrary bit integer in the range. If is missing, then it is automatically assigned to. It is expected that other information about tenants such as auth tokens, tenant names, limits, accounting, etc. is stored in a separate relational database. This database must be managed by a separate service sitting in front of VictoriaMetrics write error rate victoria such as vmauth or vmgateway. Contact us if you need assistance with such service.
Tenants are automatically created when the first data point is written into the given tenant.
Data for all the tenants is evenly spread among available nodes, write error rate victoria. This guarantees even load among nodes when different tenants have different amounts of data and different query load.
The database performance and resource usage doesn't depend on the number of tenants. It depends mostly on the total number of active time series in all the tenants. A time series is considered active if it received at least a single sample during the last hour or it has been touched by queries during the last hour.
VictoriaMetrics doesn't support querying multiple tenants in a single request.
Compiled binaries for the cluster version are available in the section of the releases page. Also see archives containing the word .
Docker images for the cluster version are available here:
Building from sources
The source code for the cluster version is available in the cluster branch.
There is no need to install Go on a host system since binaries are built inside the official docker container for Go. This allows reproducible builds. So install docker and run the following command:
Production binaries are built into statically linked binaries. They are put into the folder with suffixes:
- Install go. The minimum supported version is Go
- Run from the repository root. It should buildand binaries and put them into the folder.
Building docker images
Run. It will build the following docker images locally:
is auto-generated image tag, which depends on source code in the repository. The may be manually set via .
By default images are built on top of alpine image in order to improve debuggability. It is possible to build an image on top of any other base image by setting it via environment variable. For example, the following command builds images on top of scratch image:
A minimal cluster must contain the following nodes:
- a single node with and flags
- a single node with
- a single node with
It is recommended to run at least two nodes for each service for high availability purposes. In this case the cluster continues working when a single node is temporarily unavailable and the remaining nodes can handle the increased workload. The node may be temporarily unavailable when the underlying hardware breaks, during software upgrades, migration or other maintenance tasks.
It is preferred to run many small nodes over a few big nodes, since this reduces the workload increase on the remaining nodes when some of nodes become temporarily unavailable.
An http load balancer such as vmauth or must be put in front of and nodes. It must contain the following routing configs according to the url format:
- requests starting with must be routed to port on nodes.
- requests starting with must be routed to port on nodes.
Ports may be altered by setting on the corresponding nodes.
It is recommended setting up monitoring for the cluster.
The following tools can simplify cluster setup:
It is possible manualy setting up a toy cluster on a single host. In this case every cluster component -and - must have distinct values for command-line flag. This flag specifies http address for accepting http requests for monitoring and profiling, write error rate victoria. node must have distinct values for the following additional command-line flags write error rate victoria order to prevent resource usage clash:
- - every node must have a dedicated data storage.
- - every node must listen for a distinct tcp address for accepting data from nodes.
- - every node must listen for a distinct tcp address for accepting requests from nodes.
Each flag values can be set through environment variables by following these rules:
- The flag must be set
- Each in flag names must be substituted by (for example will translate to )
- For repeating flags, an alternative syntax can be used by joining the different values into one using as separator (for example will translate to )
- It is possible setting prefix for environment vars with. For instance, ifthen env vars must be prepended with
By default and nodes use unencrypted connections to nodes, since it is assumed that all the cluster components run in a protected environment. Enterprise version of VictoriaMetrics provides optional support for mTLS connections between cluster components. Pass command-line flag toand nodes in order to enable mTLS protection, write error rate victoria. Additionally,and must be configured with mTLS certificates viacommand-line options. These certificates are mutually verified when and dial .
The following optional command-line flags related to mTLS are supported:
- can be set atand in order to disable write error rate victoria certificate verification. Note that this breaks security.
- can be set atwrite error rate victoria, and for verifying peer certificates issued with custom certificate authority. By default system-wide certificate authority is used for peer certificate verification.
- can be set to the list of supported TLS cipher suites at. See the list of supported TLS cipher suites.
When runs with command-line option, then it can be configured with options similar to for accepting connections from top-level nodes in multi-level cluster setup.
See these docs on how to set up mTLS in VictoriaMetrics cluster.
Enterprise version of VictoriaMetrics can be downloaded and evaluated for free from the releases page.
All the cluster components expose various metrics in Prometheus-compatible format at page on the TCP port set in command-line flag, write error rate victoria. By default the following TCP ports are used:
It is recommended setting up vmagent or Prometheus to scrape pages from all the cluster components, so they can be monitored and analyzed with the official Grafana dashboard for VictoriaMetrics cluster or an alternative dashboard for VictoriaMetrics cluster. Graphs on these dashboards contain useful hints - hover the icon at the top left corner of each graph in order to read it.
It is recommended setting up alerts in vmalert or in Prometheus from this config.
nodes can be configured with limits on the number of unique time series across all the tenants with the following command-line flags:
- is the limit on the number of active time series during the last hour.
- is the limit on the number of unique time series during the day. This limit can be used for limiting daily time series churn rate.
Note that these limits are set and applied individually per each node in the cluster. So, if the cluster has nodes, then the cluster-level limits will be times bigger than the per- limits.
See more details about cardinality limiter in these docs.
See trobuleshooting docs.
nodes automatically switch to readonly mode when the directory pointed by contains less than of free space. nodes stop sending data to such nodes and start re-routing the data to the remaining nodes.
- URLs for data ingestion:where:
- is an arbitrary bit integer identifying namespace for data ingestion (aka tenant), write error rate victoria. It is possible to set it aswhere is also arbitrary bit integer. If isn't set, then it equals to .
- may have the following values:
- URLs for Prometheus querying API:where:
- is an arbitrary number identifying data namespace for the query (aka tenant)
- may have the following values:
- - performs PromQL instant query.
- - performs PromQL range query.
- - performs series query.
- - returns a list of label names.
- - returns values for the given according to API.
- - returns federated metrics.
- - exports raw data in JSON line format. See this article for details.
- - exports raw data in native binary format. It may be imported into another VictoriaMetrics via (see above).
- - exports data in CSV. It may be imported into another VictoriaMetrics via (see above).
- - returns the total number of series.
- - for time series stats. See these docs for details.
- - for currently executed active queries. Note that every maintains an independent list of active queries, which is returned in the response.
- - for listing the most frequently executed queries and queries taking the most duration.
- URLs for Graphite Metrics API:where:
- is an arbitrary number identifying data namespace for query (aka tenant)
- may have the following values:
- - implements Write error rate victoria Render API. See these docs. This functionality is available in Enterprise package. Enterprise binaries can be downloaded and evaluated for free from the releases page.
- - searches Graphite metrics. See these docs.
- - expands Graphite metrics. See these docs.
- - returns all the metric names. See these docs.
- - registers time series. See these docs.
- - register multiple time series. See these docs.
- - returns tag names. See these docs.
- - returns tag values for the given. See these docs.
- - returns series matching the given. See these docs.
- - returns tags matching the given and/or. See these docs.
- - returns tag values matching the given and/or. See these docs.
- - deletes series matching the given. See these docs.
URL with basic Web UI: .
URL for query stats across all tenants:. It lists with the most frequently executed queries and queries taking the most duration.
URL for time series deletion:. Note that the handler should be used only in exceptional cases such as deletion of accidentally ingested incorrect time series. It shouldn't be used on a regular basis, since it carries non-zero overhead.
URL for accessing vmalert's UI: error code is 10054. This URL works only write error rate victoria flag is set. See more about vmalert here.
- nodes provide the following HTTP endpoints on port:
- - initiate forced compactions on the given node.
- - create instant snapshot, which can be used for backups in background. Snapshots are created in folder, where is the corresponding command-line flag value.
- - list available snasphots.
- - delete the given snapshot.
- - delete all the snapshots.
Snapshots may be created independently on each node. There is no need in synchronizing snapshots' creation across nodes.
Cluster resizing and scalability
Cluster performance and capacity can be scaled up in two ways:
- By adding more resources (CPU, RAM, disk IO, disk space, network bandwidth) to existing nodes in the cluster (aka vertical scalability).
- By adding more nodes to the cluster (aka horizontal scalability).
General recommendations for cluster scalability:
- Adding more CPU and RAM to existing nodes improves the performance for heavy queries, which process big number of time series with big number of raw samples. See this article on how to detect and optimize heavy queries.
- Adding more nodes increases the number of active time series the cluster can handle. This also increases query performance over time series with high churn rate. The cluster stability is also improved with the number of nodes, since active nodes need to handle lower additional workload when some of nodes become unavailable.
- Adding more CPU and RAM to existing nodes increases the number of active time series the cluster can handle. It is preferred to add more nodes over adding more CPU and RAM to existing nodes, since higher number of nodes increases cluster stability and improves query performance over time series with high churn rate.
- Adding more nodes increases the maximum possible data ingestion speed, since the ingested data may be split among bigger number of nodes.
- Adding more nodes increases the maximum possible queries rate, since the incoming concurrent requests may be split among bigger number of nodes.
Steps to add node:
- Start new node with the same as existing nodes in the cluster.
- Gradually restart all the nodes with new arg containing .
- Gradually restart all the nodes with new arg containing .
Updating / reconfiguring cluster nodes
All the node write error rate victoria -and - may be updated via graceful shutdown. Send signal to the corresponding process, wait until it finishes and then start new version with new configs.
There are the following cluster update / upgrade approaches exist:
No downtime strategy
Gracefully restart every node in the cluster one-by-one with the updated config / upgraded binary.
It is recommended restarting the nodes in the following order:
- Restart nodes.
- Restart nodes.
- Restart nodes.
This strategy allows upgrading the cluster without downtime if the following conditions are met:
- The cluster has at least a pair of nodes of each type -andso it can continue accept new data and serve incoming requests when a single node is temporary unavailable during its restart. See cluster availability docs for details.
- The cluster has enough compute resources (CPU, RAM, network bandwidth, disk IO) for processing the current workload when a single node of any type (, or ) is temporarily unavailable during its restart.
The updated config / upgraded binary is compatible with the remaining components in the write error rate victoria. See the CHANGELOG for compatibility notes between different releases.
If at least a single condition isn't met, then the rolling restart may result in cluster unavailability during the config update / version upgrade. In this case the following strategy is recommended.
Minimum downtime strategy
- Gracefully stop all the and nodes in parallel.
- Gracefully restart all the nodes in parallel.
- Start all the and nodes in parallel.
The cluster is unavailable for data ingestion and querying when performing the steps above. The downtime is minimized by restarting cluster nodes in parallel at every step above. The strategy has the following benefits comparing to startegy:
- It allows performing config update / version upgrade with minimum disruption when the previous config / version is incompatible with the new config / version.
- It allows perorming config update / version upgrade with minimum disruption when the cluster has no enough compute resources (CPU, RAM, disk IO, network bandwidth) for rolling upgrade.
- It allows minimizing the duration of config update / version ugprade for clusters with big number of nodes of for clusters with big nodes, which may take long time for graceful restart.
VictoriaMetrics cluster architecture prioritizes availability over data consistency. This means that the terror hardcore hoodies remains available for data ingestion and data querying if some of its components are temporarily unavailable.
VictoriaMetrics cluster remains available if the following conditions are met:
HTTP load balancer must stop routing requests to unavailable and nodes.
At least a single node must remain available in the cluster for write error rate victoria data ingestion workload. The remaining active nodes must have enough compute capacity (CPU, RAM, network bandwidth) for handling the current data ingestion workload. If the remaining active nodes have no enough resources for processing the data ingestion workload, then arbitrary delays may occur during data ingestion, write error rate victoria. See capacity planning and cluster resizing docs for more details.
At least a single node must remain available in the cluster for processing query workload. The remaining active nodes must have enough compute capacity (CPU, RAM, network bandwidth, disk IO) for handling the current query workload. If the remaining active nodes have no enough resources for processing query workload, then arbitrary failures and delays may occur during query processing. See capacity planning and cluster resizing docs for more details.
At least a single node must remain available in the cluster for accepting newly ingested data and for processing incoming queries. The remaining active nodes must have enough compute capacity (CPU, write error rate victoria, RAM, network bandwidth, write error rate victoria, disk IO, free disk space) for handling the current workload. If the remaining active nodes write error rate victoria no enough resources for processing query workload, then arbitrary failures and delay may occur during data ingestion and query processing. See capacity planning and cluster resizing docs for more details.
The cluster works in the following way when some of nodes are unavailable:
re-routes newly ingested data from unavailable nodes to remaining healthy nodes. This guarantees that the newly ingested data is properly saved if the healthy nodes have enough CPU, RAM, disk IO and network bandwidth for processing the increased data ingestion workload. spreads evenly the additional data among the healthy nodes in order to spread evenly the increased load on these nodes.
continues serving queries if at least a single nodes is available. It marks responses as partial for queries served from the remaining healthy nodes, since such responses may miss historical data stored on the temporarily unavailable nodes. Every partial JSON response contains option. If you prefer consistency over availability, then run nodes with command-line flag. In this case returns an error if at least a single node is unavailable, write error rate victoria. Another option is to pass query arg to requests to nodes.
doesn't serve partial responses for API handlers returning raw datapoints - endpoints, since users usually expect this data is always complete.
Data replication can be used for increasing storage durability. See these docs for details.
VictoriaMetrics uses lower amounts of CPU, RAM and storage space on production workloads compared to competing solutions (Prometheus, Thanos, write error rate victoria, Cortex, TimescaleDB, InfluxDB, QuestDB, M3DB) according to our case studies.
Each node type -and - can run on the most suitable hardware. Cluster capacity scales linearly with the available resources. The needed amounts of CPU and RAM per each node type highly depends on the workload - the number of active time series, series churn rate, query types, query qps, etc. It is recommended setting up a test VictoriaMetrics cluster for your production workload and iteratively scaling per-node resources and the number of nodes per node type until the cluster becomes stable. It is recommended setting up monitoring for the cluster. It helps determining bottlenecks in cluster setup. It is also recommended following the troubleshooting docs.
The needed storage space for the given retention (the retention is set via command-line flag at ) can be extrapolated from postgresql error codes space usage in a test run. For example, if the storage space usage is 10GB after a day-long write error rate victoria run on a production workload, then it will need at least of disk space for (days retention period). Storage space usage can be monitored with write error rate victoria official Grafana dashboard for VictoriaMetrics cluster.
It is recommended leaving the following amounts of spare resources:
- 50% of free RAM across all the node types for reducing the probability of OOM (out of memory) crashes and slowdowns during temporary spikes in workload.
- 50% of spare CPU across all the node types for reducing the probability of slowdowns during temporary spikes in workload.
- At least 20% of free storage space at the directory pointed by command-line flag at nodes. See also command-line flag description for vmstorage.
Some capacity planning tips for VictoriaMetrics cluster:
- The replication increases the amounts of needed resources for the cluster by up to times where is replication factor. This is because stores copies of every ingested sample on distinct nodes. These copies are de-duplicated by during querying, write error rate victoria. The most cost-efficient and performant solution for data durability is to rely on replicated durable persistent disks such as Google Compute persistent disks instead of using the replication at VictoriaMetrics level.
- It is recommended to run a cluster with big number of small nodes instead of a cluster with small number of big nodes. This increases chances that the cluster remains available and stable when some of nodes are temporarily unavailable during maintenance events such as upgrades, configuration changes or migrations. For example, when a cluster contains 10 nodes and a single node becomes temporarily unavailable, then the workload on the remaining 9 nodes increases by. When a cluster contains 3 nodes and a single node becomes temporarily unavailable, then the workload on the remaining 2 nodes increases by. The remaining nodes may have no enough free capacity for handling the increased workload. In this case the cluster may become overloaded, which may result to decreased availability and stability.
- Cluster capacity for active time series can be increased by increasing RAM and CPU resources per each node or by adding new nodes.
- Query latency can be reduced by increasing CPU resources per each node, since each incoming query is processed by a single node. Performance for heavy queries scales with the number of available CPU cores at node, since processes time series referred by the query on all the available CPU cores.
- If the cluster needs to process incoming queries at a high rate, then its capacity can be increased by adding more nodes, so incoming queries could be spread among bigger number of nodes.
- By default compresses the data it sends to in order to reduce network bandwidth usage. The compression takes additional CPU resources at. If nodes have limited CPU, then the compression can be disabled by passing command-line flag at nodes.
- By default compresses the data it sends to during queries in order to reduce network bandwidth usage. The compression takes additional CPU resources at. If nodes have limited CPU, then the compression can be disabled by passing command-line flag at nodes.
See also resource usage limits docs.
Resource usage limits
By default cluster components of VictoriaMetrics are tuned for an optimal resource usage under typical workloads. Some workloads may need fine-grained resource usage limits, write error rate victoria. In these cases the following command-line flags may be useful:
- and limit the amounts of memory, which may be used for various internal caches at all the cluster components of VictoriaMetrics -and. Note that VictoriaMetrics components may use more memory, write error rate victoria, since these flags don't limit additional memory, which may be needed on a per-query basis.
- at component limits the number of unique time series a single query can find and process. passes the limit to component, write error rate victoria, which keeps in memory some metainformation about the time series located by each query and spends some CPU time for processing the found time series. This means that the maximum memory usage and CPU usage a single query can use at is proportional to .
- at limits the duration of a single query. If the query takes longer than the given duration, then it is canceled. This allows saving CPU and RAM at and when executing unexpected heavy queries.
- at limits the number of concurrent requests a single node can process. Bigger number of concurrent requests usually means bigger memory usage at both and. For example, if a single query needs MiB of additional memory during its execution, then concurrent queries may need of additional memory. So it is better to limit the number of concurrent queries, while suspending additional incoming queries if the concurrency limit is reached. provides command-line flag for limiting the max wait time for suspended queries.
- at limits the number of raw samples the query can process per each time series. sequentially processes raw samples per each found time series during the query. It unpacks raw samples on the selected time range per each time series into memory and then applies the given rollup function. The command-line flag allows limiting memory usage at in the case when the query is executed on a time range, which contains hundreds of millions of raw samples per each located time series.
- at limits the number of error 017 undefined symbol file samples a single query can process. This allows limiting CPU usage at for heavy queries.
- limits the number of calculated points, which can be returned per each matching time series from range query.
- limits the number of calculated points, which can be generated per each matching time series during subquery evaluation.
- at limits the number of time series, which may be returned from /api/v1/series. This endpoint is used mostly by Grafana for auto-completion of metric names, label names and label values. Queries to this endpoint may take big amounts of CPU time and memory at and when the database contains big number of unique time series because of high churn rate. In this case it might be useful to set the to quite low value in order limit CPU and memory usage.
- at limits the number of items, which may be returned write error rate victoria /api/v1/labels. This endpoint is used mostly by Grafana for auto-completion of label names. Queries to this endpoint may take big amounts of CPU time and memory at and when the database contains big number of unique time series because of high churn rate. In this case it might be useful to set the to quite low value in order to limit CPU and memory usage.
- at limits the number of items, which may be returned from /api/v1/label/…/values. This endpoint is used mostly by Grafana for auto-completion of label values. Queries to this endpoint may take big amounts of CPU time and memory at and when the database contains big number of unique time series because of high churn rate. In this case it might be useful to set the to quite low value in order to limit CPU and memory usage.
- at can be used for delphi xe runtime error 216 the number of time series seen per day aka time series churn rate. See cardinality limiter docs.
- at can be used for limiting the number of active time series. See cardinality limiter docs.
See also capacity planning docs and cardinality limiter in vmagent.
The database is considered highly available if it continues accepting new data and processing incoming queries when some of its components are temporarily unavailable. VictoriaMetrics cluster is highly available according to this definition - see cluster availability docs.
It is recommended to run all the components for a single cluster in the same subnetwork with high bandwidth, low latency and low error rates. This improves cluster performance and availability, write error rate victoria. It isn't recommended spreading components for a single cluster across multiple availability zones, since cross-AZ network usually has lower bandwidth, higher latency and higher error rates comparing the network inside a single AZ.
If you need multi-AZ setup, then it is recommended running independed clusters in each AZ and setting up vmagent in front of these clusters, so it could replicate incoming data into all the cluster - see these docs for details. Then an additional nodes can be configured for reading the data from multiple clusters according to these docs.
Multi-level cluster setup
nodes can be queried by other nodes if they run with command-line flag. For example, if is started withthen it can accept queries from another nodes at TCP port in the same way as nodes do. This allows chaining nodes and building multi-level cluster topologies. For example, the top-level node can query second-level nodes in different availability zones (AZ), while the second-level nodes can query nodes in local AZ.
nodes can accept data from another nodes if they run with command-line flag. For example, if is started withdirt 3 steam error it can accept data from another nodes at TCP port in the same way as nodes do. This allows chaining nodes and building multi-level cluster topologies. For example, the top-level node can replicate data among the second level write error rate victoria nodes located in distinct availability zones (AZ), write error rate victoria, while the second-level nodes can spread the data among nodes in local AZ.
The multi-level cluster setup for nodes has the following shortcomings because of synchronous replication and data sharding:
- Data ingestion speed is limited by the slowest link to AZ.
- nodes at top level re-route incoming data to the remaining AZs when some AZs are temporariliy unavailable, write error rate victoria. This results in data gaps at AZs which were temporarily unavailable.
These issues are addressed by vmagent when it runs in multitenancy mode. buffers data, write error rate victoria, which must be sent to a particular AZ, when this AZ is temporarily unavailable. The buffer is stored on disk. The buffered data is sent to AZ as soon as it becomes available.
Helm chart simplifies managing cluster version of VictoriaMetrics in Kubernetes, write error rate victoria. It is available in the helm-charts repository.
K8s operator simplifies managing VictoriaMetrics components in Kubernetes.
Replication and data safety
By default VictoriaMetrics offloads replication to the underlying storage pointed by such as Google compute persistent disk, which guarantees data durability. VictoriaMetrics supports application-level replication if replicated durable persistent disks cannot be used write error rate victoria some reason.
The replication can be enabled by passing command-line flag to. This instructs to store copies for every ingested sample on distinct nodes. This guarantees that all the stored data remains available for querying if up to nodes are unavailable.
The cluster must contain at least nodes, where is replication factor, in order to maintain the given replication factor for newly ingested data when of storage nodes are unavailable.
VictoriaMetrics stores timestamps with millisecond precision, so command-line flag must be passed to nodes when the write error rate victoria is enabled, so they could de-duplicate replicated samples obtained from distinct nodes during querying. If duplicate data is pushed to VictoriaMetrics from identically configured vmagent instances or Prometheus instances, then the must be set to from scrape configs according to deduplication docs.
Note that replication doesn't save from disaster, so it is recommended performing regular backups. See these docs for details.
Note that the replication increases resource usage - CPU, RAM, disk space, network bandwidth - by up to times, because stores copies of incoming data to distinct nodes and needs to de-duplicate the replicated data obtained from nodes during querying. So it is more cost-effective to offload the replication to underlying replicated durable storage pointed by such as Google Compute Engine persistent disk, which is protected from data loss and data corruption. It also provides consistently high performance and may be resized without downtime. HDD-based persistent disks should be enough for the majority of use cases, write error rate victoria. It is recommended using durable replicated persistent volumes in Kubernetes.
Cluster version of VictoriaMetrics supports data deduplication in the same way as single-node version do. See these docs for details, write error rate victoria. The only difference is that the same command-line flag value must be passed to both and nodes because of the following aspects:
By default tries to route all the samples for a single time series to a single node. But samples for a single time series can be spread among multiple nodes under certain conditions:
- when adding/removing nodes. Then new samples for a part of time series will be routed to another nodes;
- when nodes are temporarily unavailable (for instance, during their restart). Then new samples are re-routed to the remaining available nodes;
- when node has no enough capacity for processing incoming data stream. Then re-routes new samples to other nodes.
It is recommended performing periodical backups from instant snapshots for protecting from user errors such as accidental data deletion.
The following steps must write error rate victoria performed for each node for creating a backup:
- Create an instant snapshot by navigating to HTTP handler. It will create snapshot and return its name.
- Archive the created snapshot from folder using vmbackup. The archival process doesn't interfere with work, so it may be performed at any suitable time.
- Delete unused snapshots via or in order to free up occupied storage space.
There is no need in synchronizing backups among all the write error rate victoria from backup:
- Stop node with .
- Restore data from backup using vmrestore into directory.
- Start node.
Downsampling is available in enterprise version of VictoriaMetrics. It is configured with command-line flag, write error rate victoria. The same flag value must be passed to both and nodes. See these docs for details.
Enterprise binaries can be downloaded and evaluated for free from the releases page.
All the cluster components provide the following handlers for profiling:
- for memory profile and for CPU profile
- for memory profile and for CPU profile
- for memory profile and for CPU profile
Example command for collecting cpu profile from (replace with hostname if needed):
Example command for collecting memory profile from (replace with hostname if needed):
It is safe sharing the collected profiles from security point of view, since they do not contain sensitive information.
vmselect is capable of proxying requests to vmalert when flag is set. Use this feature for the following cases:
- for proxying requests from Grafana Alerting UI;
- for accessing vmalert's UI through vmselect's Web interface.
For accessing vmalert's UI through vmselect configure flag and visit link.
Community and write error rate victoria are open to third-party pull requests provided they follow the KISS design principle:
- Prefer simple code and architecture.
- Avoid complex abstractions.
- Avoid magic code and fancy algorithms.
- Avoid big external dependencies.
- Minimize the number of twonky syntax error unexpected parts in the distributed system.
- Avoid automated decisions, which may hurt cluster availability, consistency or performance.
Adhering to the principle simplifies the resulting code and architecture, so it can be reviewed, understood and verified by many people.
Due tocluster version of VictoriaMetrics has no the following "features" popular in distributed computing world:
- Fragile gossip protocols, write error rate victoria. See failed attempt in Thanos.
- Hard-to-understand-and-implement-properly Paxos protocols.
- Complex replication schemes, which may go nuts in unforeseen edge cases. See replication docs for details.
- Automatic data reshuffling between storage nodes, which may hurt cluster performance and availability.
- Automatic cluster resizing, which may cost you a lot of money if improperly configured.
- Automatic discovering and addition of new nodes in the cluster, which may mix data between dev and prod clusters :)
- Automatic leader election, which may result in split brain disaster on network errors.
Report bugs and propose new features here.
List of command-line flags
List of command-line flags for vminsert
Below is the output for :
List of command-line flags for vmselect
Below is the output for :
List of command-line flags for vmstorage
Below is the output for :
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- Please don't use any other font instead of suggested.
- There should be sufficient clear space around the logo.
- Do not change spacing, alignment, or relative locations of the design elements.
- Do not change the proportions of any of the design elements or the design itself. You may resize as needed but must retain all proportions.
How to Fix the Steam Disk Write Error
Restart Steam. The easiest way to rule out a temporary issue is to close the Steam client, reopen it, and then download or play it again.
Restart the computer. If closing and reopening Steam doesn't resolve the issue, rebooting the PC could fix it by closing ongoing processes that might interfere with Steam.
Why Restarting Something Tends to Fix Most Problems
Remove write protection from the drive. Write protection prevents a computer from altering or adding files to a folder or an entire drive. If you believe this to be the source of the problem, verify which drive your Steam games are stored on, and then remove write protection from that drive.
Turn off the read-only setting for the Steam folder. If the Steam directory is set to read-only, then the whole directory is write-protected. Go to the Steam folder properties and make sure the read-only setting isn't selected.
Run Steam as an administrator. Running software as an administrator gives it extra permissions and can fix several odd problems.
Delete corrupted files. When something goes wrong while Steam is downloading a game, it may create a corrupted file that causes the Steam disk write error. To fix this problem, go to the main Steam di keygen error has occurred and open the steamapps/common directory. If you see a file with the same name as the game you're trying to play that is 0 KB in size, delete it and attempt to download or launch the game again.
Verify the integrity of the game files. In your Steam library, right-click the game and select Properties. Then, go to the Local Files tab and select Verify Integrity of Game Files. If Steam finds any corrupt files, it automatically replaces those files.
If your game uses a launcher that downloads additional updates, do not complete this step. Doing so will replace your updated game with the base launcher, and you will then need to re-download the updates through the launcher.
Clear the Steam download cache. If the Steam download cache is corrupted, it can cause disk write errors. To fix this problem, open Steam and navigate to Steam > Settings > Downloads > Clear Download Cache.
Move Steam to a different drive. In some cases, there may be a problem with the drive that prevents Steam from writing to it. If you have multiple write error rate victoria or partitions, move the Steam installation folder to a different drive.
If this step resolves the Steam disk write error, check the original drive for errors.
Check the drive for errors. In some cases, this process can identify bad sectors and tell Windows to ignore those sectors in the future. If the problem persists or gets worse, you may need to replace the hard drive.
Disable the antivirus program or add exceptions. In rare instances, antivirus programs can incorrectly identify Steam as a threat and prevent it from downloading and saving game data. If the Steam disk write error goes away waste motor error samsung printer the antivirus disabled, add an exception for Steam in the antivirus scans.
How to Disable Norton Antivirus
Disable the firewall or add exceptions. If temporarily disabling the firewall fixes the problem, add an exception to the Windows firewall.
How to Disable the Windows Firewall
Contact Steam for help. Steam's technical support team can walk you through potential solutions for your specific problem. You can also find help in the Steam Community forum.