Automate your configuration with observability as code

.
├── LICENSE
├── README.md
├── important.tf
├── variables.tf
├── outputs.tf

# get the New Relic terraform supplier
terraform {
  required_version = "~> 1.0"
  required_providers {
    newrelic = {
      supply  = "newrelic/newrelic"
    }
  }
}

# configure the New Relic supplier
supplier "newrelic" {
  account_id = <Your Account ID>
  api_key = <Your Consumer API Key>    # normally prefixed with 'NRAK'
  area = "US"                    # Legitimate areas are US and EU
}

# New Relic One Dashboard
useful resource "newrelic_one_dashboard" "exampledash" {
    # The title of the dashboard.
  identify = "New Relic Terraform Instance"

    # A nested block that describes a web page
  web page {
        # The identify of the web page.
    identify = "New Relic Terraform Instance"

        # A nested block that describes a Billboard widget
    widget_billboard {
      title = "Requests per minute"
      row = 1
      column = 1
      width = 6
      peak = 3

            # A nested block that describes a NRQL Question
      nrql_query {
        question = "FROM Transaction SELECT price(depend(*), 1 minute)"
      }
    }
  }
}

# get the New Relic terraform supplier
terraform {
  required_version = "~> 1.0"
  required_providers {
    newrelic = {
      supply  = "newrelic/newrelic"
    }
  }
}

# configure the New Relic supplier
supplier "newrelic" {
  account_id = (var.nr_account_id)
  api_key = (var.nr_api_key)    # normally prefixed with 'NRAK'
  area = (var.nr_region)      # Legitimate areas are US and EU
}

# useful resource to create, replace, and delete dashboards in New Relic
useful resource "newrelic_one_dashboard" "dashboard_name" {
  identify = "O11y_asCode-FoodMe-Dashboards-TF"

  # determines who can see the dashboard in an account
  permissions = "public_read_only"

  web page {
    identify = "Dashboards as Code"

    widget_markdown {
      title = "Golden Indicators - Latency"
      row = 1
      column = 1
      width = 4
      peak = 3

      textual content = "## The 4 Golden Indicators - Latencyn---n#### The time it takes to service a request. It’s essential to tell apart between the latency of profitable requests and the latency of failed requests. nn#### For instance, an HTTP 500 error triggered attributable to lack of connection to a database or different important backend could be served in a short time; nevertheless, as an HTTP 500 error signifies a failed request, factoring 500s into your general latency would possibly end in deceptive calculations. nn#### Alternatively, a gradual error is even worse than a quick error! Subsequently, it’s essential to trace error latency, versus simply filtering out errors."
    }

    widget_line {
      title = "Golden Indicators - Latency - FoodMe - Line"
      row = 1
      column = 5
      width = 4
      peak = 3

      nrql_query {
        question = "SELECT common(apm.service.overview.net) * 1000 as 'Latency' FROM Metric WHERE appName like '%FoodMe%' since half-hour in the past TIMESERIES AUTO"
      }
    }

    widget_stacked_bar {
      title = "Golden Indicators - Latency - FoodMe - Stacked Bar"
      row = 1
      column = 9
      width = 4
      peak = 3

      nrql_query {
        question = "SELECT common(apm.service.overview.net) * 1000 as 'Latency' FROM Metric WHERE appName like '%FoodMe%' since half-hour in the past TIMESERIES AUTO"
      }
    }

    widget_markdown {
      title = "Golden Indicators - Errors"
      row = 4
      column = 1
      width = 4
      peak = 3

      textual content = "## The 4 Golden Indicators - Errorsn---nn#### The speed of requests that fail, both explicitly (e.g., HTTP 500s), implicitly (for instance, an HTTP 200 success response, however coupled with the mistaken content material), or by coverage (for instance, "In case you dedicated to one-second response instances, any request over one second is an error").n n#### The place protocol response codes are inadequate to precise all failure circumstances, secondary (inside) protocols could also be mandatory to trace partial failure modes. nn#### Monitoring these circumstances could be drastically totally different: catching HTTP 500s at your load balancer can do a good job of catching all fully failed requests, whereas solely end-to-end system assessments can detect that you just’re serving the mistaken content material."
    }

    widget_area {
      title = "Golden Indicators - Errors - FoodMe - Space"
      row = 4
      column = 5
      width = 4
      peak = 3

      nrql_query {
        question = "SELECT (depend(apm.service.error.depend) / depend(apm.service.transaction.length))*100 as 'Errors' FROM Metric WHERE (appName like '%FoodMe%') AND (transactionType="Internet") SINCE half-hour in the past TIMESERIES AUTO"
      }
    }

    widget_billboard {
      title = "Golden Indicators - Errors - FoodMe - Billboard Evaluate With"
      row = 4
      column = 9
      width = 4
      peak = 3

      nrql_query {
        question = "SELECT (depend(apm.service.error.depend) / depend(apm.service.transaction.length))*100 as 'Errors' FROM Metric WHERE (appName like '%FoodMe%') AND (transactionType="Internet") SINCE half-hour in the past COMPARE WITH half-hour in the past"
      }
    }

    widget_markdown {
      title = "Golden Indicators - Visitors"
      row = 7
      column = 1
      width = 4
      peak = 3

      textual content = "## The 4 Golden Indicators - Trafficn---nn#### A measure of how a lot demand is being positioned in your system, measured in a high-level system-specific metric. nn#### For an internet service, this measurement is normally HTTP requests per second, maybe damaged out by the character of the requests (e.g., static versus dynamic content material). nn#### For an audio streaming system, this measurement would possibly deal with community I/O price or concurrent periods. nn#### For a key-value storage system, this measurement could be transactions and retrievals per second."
    }

    widget_table {
      title = "Golden Indicators - Visitors - FoodMe - Desk"
      row = 7
      column = 5
      width = 4
      peak = 3

      nrql_query {
        question = "SELECT price(depend(apm.service.transaction.length), 1 minute) as 'Visitors' FROM Metric WHERE (appName LIKE '%FoodMe%') AND (transactionType="Internet") FACET path SINCE half-hour in the past"
      }
    }

    widget_pie {
      title = "Golden Indicators - Visitors - FoodMe - Pie"
      row = 7
      column = 9
      width = 4
      peak = 3

      nrql_query {
        question = "SELECT price(depend(apm.service.transaction.length), 1 minute) as 'Visitors' FROM Metric WHERE (appName LIKE '%FoodMe%') AND (transactionType="Internet") FACET path SINCE half-hour in the past"
      }
    }

    widget_markdown {
      title = "Golden Indicators - Saturation"
      row = 10
      column = 1
      width = 4
      peak = 3

      textual content = "## The 4 Golden Indicators - Saturationn---nn#### How "full" your service is. A measure of your system fraction, emphasizing the sources which can be most constrained (e.g., in a memory-constrained system, present reminiscence; in an I/O-constrained system, present I/O). Be aware that many methods degrade in efficiency earlier than they obtain 100% utilization, so having a utilization goal is important.nn#### In advanced methods, saturation could be supplemented with higher-level load measurement: can your service correctly deal with double the site visitors, deal with solely 10% extra site visitors, or deal with even much less site visitors than it presently receives? For quite simple providers that haven't any parameters that alter the complexity of the request (e.g., "Give me a nonce" or "I would like a globally distinctive monotonic integer") that not often change configuration, a static worth from a load check could be enough. nn#### As mentioned within the earlier paragraph, nevertheless, most providers want to make use of oblique indicators like CPU utilization or community bandwidth which have a recognized higher sure. Latency will increase are sometimes a number one indicator of saturation. Measuring your 99th percentile response time over some small window (e.g., one minute) may give a really early sign of saturation.nn#### Lastly, saturation can also be involved with predictions of impending saturation, corresponding to "It seems to be like your database will fill its laborious drive in 4 hours.""
    }

    widget_line {
      title = "Golden Indicators - Saturation - CPU & Reminiscence - Multi-Queries"
      row = 10
      column = 5
      width = 4
      peak = 3

      nrql_query {
        question = "SELECT price(sum(apm.service.cpu.usertime.utilization), 1 second) * 100 as 'cpuUsed' FROM Metric WHERE appName LIKE '%FoodMe%' SINCE half-hour in the past TIMESERIES AUTO"
      }

      nrql_query {
        question = "SELECT common(apm.service.reminiscence.bodily) * price(depend(apm.service.occasion.depend), 1 minute) / 1000 as 'memoryUsed %' FROM Metric WHERE appName LIKE '%FoodMe%' SINCE half-hour in the past TIMESERIES AUTO"
      }
    }

    widget_line {
      title = "Golden Indicators - Saturation - Reminiscence - Line Evaluate With"
      row = 10
      column = 9
      width = 4
      peak = 3

      nrql_query {
        question = "SELECT common(apm.service.reminiscence.bodily) * price(depend(apm.service.occasion.depend), 1 minute) / 1000 as 'memoryUsed %' FROM Metric WHERE appName LIKE '%FoodMe%' SINCE half-hour in the past COMPARE WITH 20 minutes in the past TIMESERIES AUTO"
      }
    }
  }
}

# your distinctive New Relic account ID
variable "nr_account_id" {
  default = "XXXXX"
}
# your Consumer API key
variable "nr_api_key" {
  default = "XXXXX"
}

# legitimate areas are US and EU
variable "nr_region" {
  default = "US"
}