parca.yaml

# Copyright 2024 Specter Ops, Inc.
#
# Licensed under the Apache License, Version 2.0
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# SPDX-License-Identifier: Apache-2.0

object_storage:
  bucket:
    type: "FILESYSTEM"
    config:
      directory: "./data"

# Optionally configure targets to be scraped. It is recommended to start
# with just Parca Agent CPU profiling and add scraping where valuable.
# Scraping tends to produce a lot more data than Parca Agent CPU which
# results in memory usage by the server.
#
scrape_configs:
  - job_name: "pprof"
    scrape_interval: "1s"
    static_configs:
      - targets: ["127.0.0.1:2112"]
# Nested under the job config:
#
# Only keep a certain type of profile from a scrape. For example the Go
# runtime memory profiles contain memory inuse-space bytes and objects as
# well as allocated space and objects. Often times inuse-space bytes is
# the one that is most interest to extract from the Go runtime.
#
# profiling_config:
#   pprof_config:
#     memory:
#       keep_sample_type:
#       - type: inuse_space
#         unit: bytes
#

# Nested under the job config:
#
# Custom scrape endpoints can be added like just like the example below.
# The profile name will be `fgprof`, and it will be scraped from the given
# path and since it is a delta profile, a query parameter
# ?seconds=<scrape-interval> will be added.
#
# profiling_config:
#   pprof_config:
#     fgprof:
#       enabled: true
#       path: /debug/pprof/fgprof
#       delta: true
#