Chronosphere uses collectors to ingest data, and utilizes push and pull
models of ingestion, depending on the data collected and the method of ingestion.Chronosphere provides the following control concepts to help manage your data you
keep only the data that’s most important to your organization.
Metrics use quotas to assign specific percentages of your total persisted writes
limit to pools of metrics. Each pool might represent teams or other logical
groupings within your organization. Use metric quotas to give each pool a specific
quota of your total persisted writes license, expressed either as a percentage or a
value in data points per second (DPPS).To learn more about these control mechanisms, see
quotas and pools.
Logs use partitions, which are slices of your log data with distinct owners.
Partitions provide a consistent structure for attributing usage and costs to the
appropriate owners in your organization so they can isolate and control independent
their parts of the business.Partitions let you apply budgets, which are optional shaping policies you can
assign to a partition to safeguard against runaway usage and overspending. Budgets
provide guardrails to combat runaway usage and overspending, and provide the
flexibility to enforce accountability at the right level of ownership. Budgets
include thresholds that define which actions to take when a threshold is exceeded.To learn more about these control mechanisms, see
control log data.
Traces use datasets as a control mechanism to organize your data and map it to
named groups relevant to your organization. Datasets can either overlap or stand
alone, and can be assigned to only a single business unit or service within
your organization.Each dataset entity lets you define a filter to assign specific chunks of data to a
particular dataset. A default, system-defined dataset exists for budgeting. You can
assign the default dataset to data that isn’t explicitly assigned to any other
dataset.To change the sampling rates of one or more datasets and to more effectively control
your persisted data, use behaviors. This shaping mechanism lets you change sampling
rates of one or more datasets without needing to write fine-grained sampling or
shaping rules.To learn more about these control mechanisms, see
sample your traces.
Collectors ingest metrics at specific intervals, based on system
configuration. This granularity of metric data can be helpful in diagnostic efforts,
but particular issues might not be served by such granularity. If you are able to
diagnose production issues using a coarser granularity of metric data, downsampling
the data reduces the amount of data persisted to the Observability Platform database.Downsample incoming data in Observability Platform using these methods:
Change the Chronosphere Collector configuration by
changing the rate
the Collector publishes metrics to the server.
Use mapping rules to downsample metrics
that aren’t aggregated.
Use rollup rules to downsample aggregated
metrics.
Over time, persisted data uses significant storage capacity. Observability Platform
performs long-term downsampling to control data
storage costs while retaining important statistics.Be aware that late arriving data
can affect downsampling.
