Introduction to Structured Data – Part 4

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Through this series of blogs (1, 2, 3) on structured data, we’ve talked about what it is, how you’re probably using it today (possibly without realizing it), and how it can be used in automation. Today, we’ll talk about storing that data in a Source of Truth, instead of using spreadsheets.

You can easily follow along with the examples in this blog by using demo.nautobot.com or by using Nautobot Lab.

Historically, network engineers have kept records about their network in spreadsheets. This has worked well, as long as the networks were simple and small. As networks grow and the data requirements grow, spreadsheets can quickly become cumbersome to maintain. This is where a source of truth comes in. A source of truth is a database that maintains the records that you require. For instance, in the first structured data blog, David gave an example of a small network in a spreadsheet. It’s small and simple to maintain, but as soon as he wanted more relational information, that spreadsheet would be difficult to maintain. What if David wanted to keep information about interface configuration, cross-connects, circuits, providers, vlans, network prefixes, access lists, route policies, advertised networks? Some of those individual items would be easy to keep on the existing spreadsheet, but all of that information together would become a burdensome task. A source of truth simplifies the relationships of this data and its maintenance.

To demonstrate this, I’ve set up the same data from the first blog into Nautobot.

Example spreadsheet from first structured data blog.

Within Nautobot, I created a region called “North Carolina”. Then I created three sites: Headquarters, Police Department (North), and Police Department (South).

Each site has the address and contact information that was listed in the spreadsheet.

Once the sites were created, I created a manufacturer object, the device types, and the device roles.

Now that all of that is entered, we’re ready to create the devices. Instead of creating the devices individually, I opted to do a bulk import by modifying the CSV file to match the fields that Nautobot would be looking for.

name,manufacturer,device_type,serial,site,device_role,status
HQ-R1,Cisco Systems,ISR 4431,KRG645782,Headquarters,access,active
HQ-R2,Cisco Systems,ISR 4431,KRG557862,Headquarters,access,active
HQ-S1,Cisco Systems,CAT3560-48PS,GRN883274,Headquarters,access,active
HQ-S2,Cisco Systems,CAT3560-48PS,GRN894532,Headquarters,access,active
PD-N-R1,Cisco Systems,ISR 4431,FOM123124,Police Department (North),access,active
PD-N-S1,Cisco Systems,CAT3560-24,GRN334213,Police Department (North),access,active
PD-S-R1,Cisco Systems,ISR 4431,FOM654231,Police Department (South),access,active
PD-S-R2,Cisco Systems,CAT3560-24,GRN888931,Police Department (South),access,active

With the devices imported, the only two attributes left from the spreadsheet are the jumphost and management ip address. The jumphost attributes can be achieved by creating a config context. From the extensibility menu, select the + button next to config context.

Within the “Add a new config context” menu, we can create config contexts that will be automatically assigned to devices that match the attributes that we assign. For example, we can assign the Regions to “North Carolina”, the Sites to “Headquarters”, and the Roles to “access”. Give the config context a name, such as “Headquarters jumphost”. The Data field accepts JSON-formatted data. Add the jumphost for the Headquarters site in the Data field.

{"jumphost": "10.20.10.2"}

Then press the “Create and Add Another” button. From here, you can add the jumphosts for the remaining sites following the same steps.

At this point, the config context for jumphosts will automatically be assigned to the devices. This can be checked by pulling up a device and selecting the “Config Context” tab.

To abstract the final attribute, we also need to create interfaces to associate with the management ip address. To do this, go to a device, drop down the “+ Add Components” menu, and select interfaces.

Add the name of the interface, drop down the menu and select the interface type, select the “enabled” and “management only” check boxes, select an interface mode, and press the “Create” button.

At this point, you will be taken to the interfaces tab of the device page. The newly created interface will be in the list of interfaces. At this point, you can assign a management ip address to the interface by pressing the “+” button.

From the “Add IP Address” page, give the device a management ip address, select the status, check the “Make this the primary IP for the device/VM” checkbox, and press the “Create” button.

With that, every bit of data from the first blog spreadsheet has been captured in the source of truth. We’ve even added an extra data point by associating the management ip address with a specific interface on each device.

With this data loaded into Nautobot, it becomes much easier to start associating other data with devices and networks. Data attributes related to routing, interfaces, access lists, route policies, and so forth can all be incorporated. Having all this data at your fingertips also creates the foundation for network automation.

Conclusion

Building and deploying networks is a data-intensive job. Using a source of truth platform, such as Nautobot, enables network engineers to define network architectures that are cohesive, consistent, and that enable automation. If you have any questions, feel free to reach out on the Network to Code Slack.

-James

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Getting Started with Python Network Libraries for Network Engineers – Part 3

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This blog post is the third in a series covering common Python libraries that can be used to interact with network devices. In this post we will cover the Scrapli Python library by Carl Montanari. Per its documentation, Scrapli is the words “scrape” and “cli” (i.e. screen scrape) squished together. Its goal is to provide a thoroughly tested, well typed, well documented, simple API that supports both synchronous and asynchronous interaction with network devices.

Differentiation from Other Libraries

Scrapli is different from other libraries in the following ways:

Scrapli provides multiple forms of transport. It defaults to using a system’s local SSH binary. This is in contrast to Netmiko, which uses Paramiko for transport. The forms of transport it supports can be found here along with a justification for the decision to allow for multiple transports and default to a system’s local SSH binary.
Scrapli supports the same platforms as NAPALM out of the box. This is a subset of the platforms supported by Netmiko. The scrapli community project provides the ability for the scrapli community to contribute to and use drivers beyond those included in the base project. The platforms supported out of the box are:
- Cisco IOS-XE
- Cisco NX-OS
- Juniper JunOS
- Cisco IOS-XR
- Arista EOS
If you’re looking to write unit/integration tests for your code, scrapli has an adjacent library called scrapli-replay that can be used to do so.

Installation

You can install Scrapli via pip install scrapli. Or, if you are using Poetry, you can use poetry add scrapli. Other methods for installing scrapli are documented here.

Getting Connected

Note: We will only cover connecting via SSH in this blog post.

To start, you’ll want to import and instantiate one of the scrapli “core” drivers from scrapli.driver.core.

Scrapli requires a hostname (IP or DNS name) and an authentication method (generally username and password) to get connected. In addition to this, you will also want to specify whether or not to use SSH strict host key checking (we pass in False below).

>>> from scrapli.driver.core import IOSXEDriver
>>>
>>> conn = IOSXEDriver(
...     host="192.0.2.3",
...     auth_username="cisco",
...     auth_password="cisco",
...     auth_strict_key=False,
... )
>>> type(conn)
scrapli.driver.core.cisco_iosxe.sync_driver.IOSXEDriver
>>> conn.open()

Note: If host strict key checking is enabled (the default), an SSH session will be permitted only to hosts that have a key defined inside of your system’s “known_hosts” file.

You can also use the Scrapli class to dynamically select and instantiate a driver (much like ConnectHandler in Netmiko) in the following way:

>>> from scrapli import Scrapli
>>>
>>> conn = Scrapli(
...     host="192.0.2.3",
...     auth_username="cisco",
...     auth_password="cisco",
...     auth_strict_key=False,
...     platform="cisco_iosxe",
...  )
>>> type(conn)
scrapli.driver.core.cisco_iosxe.sync_driver.IOSXEDriver
>>> conn.open()

A list of the basic driver arguments can be found here.

Sending Commands

Once you have instantiated your Driver object, you can send single show commands via the .send_command() method. You will use the same command syntax you would type in if you were directly connected to the device via SSH:

>>> response = conn.send_command("show ip interface brief")
>>> print(response.result)
Interface              IP-Address      OK? Method Status                Protocol
FastEthernet0          unassigned      YES NVRAM  down                  down
GigabitEthernet1/0/1   192.0.2.3       YES unset  up                    up
GigabitEthernet1/0/2   unassigned      YES unset  up                    up
GigabitEthernet1/0/3   unassigned      YES unset  up                    up
>>> print(response.failed)
False

Likewise, you can send multiple commands using the .send_commands() method.

>>> response = conn.send_commands(["show ip interface brief", "show running-config | include hostname"])
>>> print(response.result[0])
Interface              IP-Address      OK? Method Status                Protocol
FastEthernet0          unassigned      YES NVRAM  down                  down
GigabitEthernet1/0/1   192.0.2.3       YES unset  up                    up
GigabitEthernet1/0/2   unassigned      YES unset  up                    up
GigabitEthernet1/0/3   unassigned      YES unset  up                    up
>>> print(response.result[1])
hostname cisco

You can also send commands from a file using the .send_commands_from_file() method.

# commands.txt
show ip int br
show run | i hostname

response = conn.send_commands_from_file("commands.txt")
>>> print(response.result[0])
Interface              IP-Address      OK? Method Status                Protocol
FastEthernet0          unassigned      YES NVRAM  down                  down
GigabitEthernet1/0/1   192.0.2.3       YES unset  up                    up
GigabitEthernet1/0/2   unassigned      YES unset  up                    up
GigabitEthernet1/0/3   unassigned      YES unset  up                    up
>>> print(response.result[1])
hostname cisco

If you want to run a command to edit the configuration, you would use the .send_configs() method instead. This method takes care of entering configuration mode for you, and it requires the commands be in a list or set:

>>> response = conn.send_configs(["interface Gi1/0/3", "no description"])
>>> print(response.result)
configure terminal
Enter configuration commands, one per line.  End with CNTL/Z.
cisco(config)#interface Gi1/0/3
cisco(config-if)#no description

Note: The send_configs() method doesn’t exit config mode like Netmiko does. It, instead, relies on the send_command() method to acquire the user exec mode prompt.

As is the case with .send_commands(), you can also send configurations from a file using the send_configs_from_file() method.

# config_changes.txt
interface Gi1/0/3
 no description

>>> response = conn.send_configs_from_file("config_changes.txt")
>>> print(response.result)
configure terminal
Enter configuration commands, one per line.  End with CNTL/Z.
cisco(config)#interface Gi1/0/3
cisco(config-if)#no description

Finally, there is a send_config() method that will parse the configuration provided as input and split it into lines, each line being sent to the device. This is useful for copying full configs over to the device.

Command Output Parsing

We’ve covered parsing strategies here on this blog before. Just as with Netmiko, Scrapli supports TextFSM, TTP, and Genie. Let’s take a quick look on how to use them with Scrapli.

TextFSM

Scrapli defines TextFSM as an “extra”. As such, the first step to using TextFSM templates with scrapli is to install the TextFSM library. You can use pip or Poetry to do so.

pip install 'scrapli[textfsm]'
poetry add 'scrapli[textfsm]'

Once TextFSM is installed, you can use the .textfsm_parse_output() method on a Scrapli response object to return the output as parsed by the NTC template. This method uses the platform inferred by the driver to set the textfsm-platform. It combines this with the command sent to the device to guess as to which template it should use to parse the returned data.

>>> response = conn.send_command("show interfaces")
>>> print(response.textfsm_parse_output())
[{'abort': '',
  'address': '381c.1ae6.cd81',
  'bandwidth': '100000 Kbit',
  'bia': '381c.1ae6.cd81',
  'crc': '0',
  'delay': '100 usec',
...

You can see the template used for this command here.

Scrapli also supports defining the template that should be used to parse the response manually. You can import and use the textfsm_parse function from scrapli.helper to do so.

>>> from scrapli.helper import textfsm_parse
>>>
>>> response = conn.send_command("show interfaces")
>>> structured_result = textfsm_parse("/path/to/template", response.result)

TTP

Scrapli also supports the TTP parsing library. As with TextFSM, you will need to install it via pip install ttp or poetry add ttp before it can be used. The TTP installation does not currently include any templates, so you will need to find or create your own and provide the path to those templates.

>>> response = conn.send_command("show interfaces")
>>> structured_result = response.ttp_parse_output(template="show_interfaces_template.ttp")
>>> pprint(structured_result)
[[[{'description': 'CAM1',
    'interface': 'GigabitEthernet1/0/1',
    'link_status': 'up',
    'protocol_status': 'up'},
   {'description': 'CAM2',
    'interface': 'GigabitEthernet1/0/2',
    'link_status': 'up',
    'protocol_status': 'up'},
...

Genie

The last parser that Scrapli currently supports is Genie. As with TextFSM and TTP, scrapli does not install Genie nor its required library, pyATS, by default, so you will need to install them separately via pip install 'pyats[library]' or poetry add 'pyats[library]'. Athough Genie parsers exist for non-Cisco platforms, In Scrapli, Genie parsers can be used only for Cisco devices.

>>> response = conn.send_command("show interfaces")
>>> structured_result = response.genie_parse_output()
>>> pprint(structured_result)
{'GigabitEthernet1/0/1': {'arp_timeout': '04:00:00',
                          'arp_type': 'arpa',
                          'bandwidth': 100000,
                          'connected': True,
                          'counters': {'in_broadcast_pkts': 41240,
...

Note: Genie does not support custom templates.

Next Steps

Perhaps you’d like to use asyncio for interactions with network devices, or learn more advanced concepts? The documentation is excellent, and a great place to start.
If you’d like more examples of common interactions using scrapli, Carl has created a directory with such examples here.
Scrapli has an ecosystem including a few adjacent tools that are worth checking out (scrapli_netconf, scrapli_nornir…etc.).

Conclusion

I hope you enjoy Scrapli. It’s an excellent tool and is my personal go-to tool for new projects in which I need to automate interactions with devices for which it has a driver.

-Phillip

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Introduction to a Telemetry Stack – Part 1

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You know that “bookending” technique in movies like Fight Club and Pulp Fiction where they open up with the chronologically last scene? Well, this is more or less the same, but instead of a movie it’s the Telemetry Stack! NTC blog post series. And this is what your network monitoring solution could look like. Well, maybe not exactly like this but you get the idea, right?

This series of blog posts that will be released during the coming weeks dives into detail on how to build a contemporary network monitoring system using widely accepted open-source materials like Telegraf, Prometheus, Grafana, and Nautobot. Also, lots of “thanks” go to Josh VanDeraa and his very detailed blog posts that have served as a huge inspiration for this series!

In part 1 of the series, we’ll focus on two aspects:

Introduction to the Telemetry Stack!
Capturing metrics and data using Telegraf

Introduction to the Telemetry Stack!

During the blog post series, we’ll explore the components that comprise the TPG (Telegraf, Prometheus, Grafana) Telemetry Stack!

Telegraf

In short, Telegraf is a metrics and events collector written in Go. Its simple architecture and plethora of built-in modules allow for easy capturing of metrics (input modules), linear processing (processor modules), and storing them to a multitude of back-end systems (output modules). For the enrichment part, Nautobot will be leveraged as the Source of Truth (SoT) that holds the additional information.

Prometheus

As already mentioned, Prometheus will be the TSDB of choice for storing our processed metrics and data.

Grafana

In order to present the data in a human-friendly form, we’ll be visualizing them using Grafana. Dashboard design is an art of its own, but we’ll attempt to present a basic set of dashboards that could serve as inspiration for creating your own.

Alertmanager

Using Grafana dashboards sprinkled with sane thresholds, we’re able to create alerting mechanisms triggered whenever a threshold is crossed.

Capturing Metrics and Data Using Telegraf

The rest of this post is dedicated on using Telegraf to get data from network devices. Now, one (or probably more) may wonder “why Telegraf?” and that’s indeed a question we also asked ourselves when designing this series. We decided to go with Telegraf based on the following factors:

it works and we like it
its configuration is comparatively easy to generate using templates
it’s a very flexible solution, allowing us to do SNMP, gNMI, and also execute Python scripts
it uses a very simple basic flow between its components

Inputs: Telegraf provides a ton of various input methods out of the box, like snmp, gnmi, and execd. These are the components that enable us to capture metrics and data from our targets. Incidentally, this is also the main topic in the second half of this post, so more details may be found there.

Processors: As with inputs, Telegraf also comes loaded with a bunch of processor modules that allow us to manipulate our collected data. In this blog post series, our focus will be normalization and enrichment of the captured metrics. This will be the main topic in the second post of the series.

Outputs: Last, once we’re happy with the processors result, we use outputs to store the transformed data. Three of the most common Time Series Databases (TSDBs), used for storing metrics are InfluxDB (from the same manufacturer as Telegraf), Elasticsearch, and of course Prometheus which will be the output used throughout the series.

For the purposes of this blog post, we’ll be using two Arista cEOS machines. So, with all that out of our way, let’s dive into our various input methods!

`[[inputs.snmp]]`

Like the old-time gray-beards that we are, we’ll begin our journey using SNMP to perform a simple metrics capture.

# ------------------------------------------------
# Input - SNMP
# ------------------------------------------------
[[inputs.snmp]]
  agents = ["ceos-02"]
  version = 2
  community = "${SNMPv2_COMMUNITY}"
  interval = "60s"
  timeout = "10s"
  retries = 3

  [inputs.snmp.tags]
    collection_method = "snmp"
    device = "ceos-02"
    device_role = "router"
    device_platform = "arista"
    site = "lab-site-01"
    region = "lab"
    net_os = "eos"
  # ------------------------------------------------
  # Device Uptime (SNMP)
  # ------------------------------------------------
  [[inputs.snmp.field]]
    name = "uptime"
    oid = "RFC1213-MIB::sysUpTime.0"

  # ----------------------------------------------
  # Device Storage Partition Table polling (SNMP)
  # ----------------------------------------------
  [[inputs.snmp.table]]
    name = "storage"

    # Partition name
    [[inputs.snmp.table.field]]
      name = "name"
      oid = "HOST-RESOURCES-MIB::hrStorageDescr"
      is_tag = true

    # Size in bytes of the data objects allocated to the partition
    [[inputs.snmp.table.field]]
      name = "allocation_units"
      oid = "HOST-RESOURCES-MIB::hrStorageAllocationUnits"

    # Size of the partition storage represented by the allocation units
    [[inputs.snmp.table.field]]
      name = "size_allocation_units"
      oid = "HOST-RESOURCES-MIB::hrStorageSize"

    # Amount of space used by the partition represented by the allocation units
    [[inputs.snmp.table.field]]
      name = "used_allocation_units"
      oid = "HOST-RESOURCES-MIB::hrStorageUsed"

Note: A detailed line-by-line explanation of the Telegraf configuration may be found in the excellent Network Telemetry for SNMP Devices blog post by Josh.

`[[inputs.gnmi]]`

Now that we’ve covered the capabilities of old-school MIB/OID-based NMS, let’s jump to what all the cool kids are playing with these days: gRPC (Remote Procedure Calls) Network Management Interface. Bit of a mouthful! The main benefits of using gNMI for telemetry are its speed and efficiency. Thanks to the magic of Telegraf, we are able to capture data with just a few more lines of code.

# ------------------------------------------------
# Input - gNMI
# ------------------------------------------------
[[inputs.gnmi]]
  addresses = ["ceos-02:50051"]
  username = "${NETWORK_AGENT_USER}"
  password = "${NETWORK_AGENT_PASSWORD}"
  redial = "20s"
  tagexclude = [
      "identifier",
      "network_instances_network_instance_protocols_protocol_name",
      "afi_safi_name",
      "path",
      "source"
  ]

  [inputs.gnmi.tags]
    collection_method = "gnmi"
    device = "ceos-02"
    device_role = "router"
    device_platform = "arista"
    site = "lab-site-01"
    region = "lab"
    net_os = "eos"

  # ---------------------------------------------------
  # Device Interface Counters (gNMI)
  # ---------------------------------------------------
  [[inputs.gnmi.subscription]]
    name = "interface"
    path = "/interfaces/interface/state/counters"
    subscription_mode = "sample"
    sample_interval = "10s"

  [[inputs.gnmi.subscription]]
    name = "interface"
    path = "/interfaces/interface/state/admin-status"
    subscription_mode = "sample"
    sample_interval = "10s"

  [[inputs.gnmi.subscription]]
    name = "interface"
    path = "/interfaces/interface/state/oper-status"
    subscription_mode = "sample"
    sample_interval = "10s"

  # ---------------------------------------------------
  # Device Interface Ethernet Counters (gNMI)
  # ---------------------------------------------------
  [[inputs.gnmi.subscription]]
    name = "interface"
    path = "/interfaces/interface/ethernet/state/counters"
    subscription_mode = "sample"
    sample_interval = "10s"

  # ----------------------------------------------
  # Device CPU polling (gNMI)
  # ----------------------------------------------
  [[inputs.gnmi.subscription]]
    name = "cpu"
    path = "/components/component/cpu/utilization/state/instant"
    subscription_mode = "sample"
    sample_interval = "10s"

  # ----------------------------------------------
  # Device Memory polling (gNMI)
  # ----------------------------------------------
  [[inputs.gnmi.subscription]]
    name = "memory"
    path = "/components/component/state/memory"
    subscription_mode = "sample"
    sample_interval = "10s"

Note: Another great blog from Josh touches on the same subjects: Monitor Your Network With gNMI, SNMP, and Grafana.

`[[inputs.execd]]`

The third and last input that we’ll examine in this blog is execd; even cooler than the gNMI cool kids! Practically, it’s a way for Telegraf to run scripts and capture the data that are output in a metrics format. In our case though, the script is in reality a container image that makes it easy to collect metrics using a multitude of different methods. In the following simple example, it is used to collect BGP information over EOS RESTful API.

# ------------------------------------------------
# Input - Execd command
# ------------------------------------------------
[[inputs.execd]]
  interval = "60s"
  signal = "SIGHUP"
  restart_delay = "10s"
  data_format = "influx"
  command = [
    '/usr/local/bin/network_agent',
    '-h',
    'ceos-02',
    '-d',
    'arista_eos',
    '-c',
    'bgp_sessions::http',  ]
  [inputs.execd.tags]
    collection_method = "execd"
    device = "ceos-02"
    device_role = "router"
    device_platform = "arista"
    site = "lab-site-01"
    region = "lab"
    net_os = "eos"

Collected Data

At this point, we’ve managed to collect various metrics and data from our target devices. We still have to process them, store them, and visualize them but these are the topics of the blog posts that will follow. For now, we may take a peek into the collected data to verify that they’ve been captured successfully, before “passing” them to the normalization/enrichment step of the process.

`[[inputs.snmp]]`

# HELP snmp_uptime Telegraf collected metric
# TYPE snmp_uptime untyped
snmp_uptime{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",net_os="eos",region="lab",site="lab-site-01"} 14082

# HELP storage_allocation_units Telegraf collected metric
# TYPE storage_allocation_units untyped
storage_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Core",net_os="eos",region="lab",site="lab-site-01"} 4096
storage_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Flash",net_os="eos",region="lab",site="lab-site-01"} 4096
storage_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Log",net_os="eos",region="lab",site="lab-site-01"} 4096
storage_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="RAM",net_os="eos",region="lab",site="lab-site-01"} 1024
storage_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="RAM (Buffers)",net_os="eos",region="lab",site="lab-site-01"} 1024
storage_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="RAM (Cache)",net_os="eos",region="lab",site="lab-site-01"} 1024
storage_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="RAM (Unavailable)",net_os="eos",region="lab",site="lab-site-01"} 1024
storage_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Root",net_os="eos",region="lab",site="lab-site-01"} 4096
storage_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Tmp",net_os="eos",region="lab",site="lab-site-01"} 4096
# HELP storage_size_allocation_units Telegraf collected metric
# TYPE storage_size_allocation_units untyped
storage_size_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Core",net_os="eos",region="lab",site="lab-site-01"} 400150
storage_size_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Flash",net_os="eos",region="lab",site="lab-site-01"} 2.5585863e+07
storage_size_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Log",net_os="eos",region="lab",site="lab-site-01"} 400150
storage_size_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="RAM",net_os="eos",region="lab",site="lab-site-01"} 1.6005976e+07
storage_size_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="RAM (Buffers)",net_os="eos",region="lab",site="lab-site-01"} 1.6005976e+07
storage_size_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="RAM (Cache)",net_os="eos",region="lab",site="lab-site-01"} 1.6005976e+07
storage_size_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="RAM (Unavailable)",net_os="eos",region="lab",site="lab-site-01"} 1.6005976e+07
storage_size_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Root",net_os="eos",region="lab",site="lab-site-01"} 2.5585863e+07
storage_size_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Tmp",net_os="eos",region="lab",site="lab-site-01"} 16384
# HELP storage_used_allocation_units Telegraf collected metric
# TYPE storage_used_allocation_units untyped
storage_used_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Core",net_os="eos",region="lab",site="lab-site-01"} 0
storage_used_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Flash",net_os="eos",region="lab",site="lab-site-01"} 7.955702e+06
storage_used_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Log",net_os="eos",region="lab",site="lab-site-01"} 14989
storage_used_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="RAM",net_os="eos",region="lab",site="lab-site-01"} 7.242028e+06
storage_used_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="RAM (Buffers)",net_os="eos",region="lab",site="lab-site-01"} 953836
storage_used_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="RAM (Cache)",net_os="eos",region="lab",site="lab-site-01"} 2.134188e+06
storage_used_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="RAM (Unavailable)",net_os="eos",region="lab",site="lab-site-01"} 4.148248e+06
storage_used_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Root",net_os="eos",region="lab",site="lab-site-01"} 7.955702e+06
storage_used_allocation_units{collection_method="snmp",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Tmp",net_os="eos",region="lab",site="lab-site-01"} 0

`[[inputs.gnmi]]`

# HELP cpu_instant Telegraf collected metric
# TYPE cpu_instant untyped
cpu_instant{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="CPU0",net_os="eos",region="lab",site="lab-site-01"} 3
cpu_instant{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="CPU1",net_os="eos",region="lab",site="lab-site-01"} 5
cpu_instant{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="CPU2",net_os="eos",region="lab",site="lab-site-01"} 3
cpu_instant{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="CPU3",net_os="eos",region="lab",site="lab-site-01"} 3

# HELP interface_in_broadcast_pkts Telegraf collected metric
# TYPE interface_in_broadcast_pkts untyped
interface_in_broadcast_pkts{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Ethernet1",net_os="eos",region="lab",site="lab-site-01"} 0
# HELP interface_in_crc_errors Telegraf collected metric
# TYPE interface_in_crc_errors untyped
interface_in_crc_errors{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Ethernet1",net_os="eos",region="lab",site="lab-site-01"} 0
# HELP interface_in_discards Telegraf collected metric
# TYPE interface_in_discards untyped
interface_in_discards{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Ethernet1",net_os="eos",region="lab",site="lab-site-01"} 0
# HELP interface_in_errors Telegraf collected metric
# TYPE interface_in_errors untyped
interface_in_errors{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Ethernet1",net_os="eos",region="lab",site="lab-site-01"} 0
# HELP interface_in_fcs_errors Telegraf collected metric
# TYPE interface_in_fcs_errors untyped
interface_in_fcs_errors{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Ethernet1",net_os="eos",region="lab",site="lab-site-01"} 0
# HELP interface_in_fragment_frames Telegraf collected metric
# TYPE interface_in_fragment_frames untyped
interface_in_fragment_frames{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Ethernet1",net_os="eos",region="lab",site="lab-site-01"} 0
# HELP interface_in_jabber_frames Telegraf collected metric
# TYPE interface_in_jabber_frames untyped
interface_in_jabber_frames{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Ethernet1",net_os="eos",region="lab",site="lab-site-01"} 0
# HELP interface_in_mac_control_frames Telegraf collected metric
# TYPE interface_in_mac_control_frames untyped
interface_in_mac_control_frames{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Ethernet1",net_os="eos",region="lab",site="lab-site-01"} 0
# HELP interface_in_mac_pause_frames Telegraf collected metric
# TYPE interface_in_mac_pause_frames untyped
interface_in_mac_pause_frames{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Ethernet1",net_os="eos",region="lab",site="lab-site-01"} 0
# HELP interface_in_multicast_pkts Telegraf collected metric
# TYPE interface_in_multicast_pkts untyped
interface_in_multicast_pkts{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Ethernet1",net_os="eos",region="lab",site="lab-site-01"} 25
# HELP interface_in_octets Telegraf collected metric
# TYPE interface_in_octets untyped
interface_in_octets{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Ethernet1",net_os="eos",region="lab",site="lab-site-01"} 4349
# HELP interface_in_oversize_frames Telegraf collected metric
# TYPE interface_in_oversize_frames untyped
interface_in_oversize_frames{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Ethernet1",net_os="eos",region="lab",site="lab-site-01"} 0
# HELP interface_in_unicast_pkts Telegraf collected metric
# TYPE interface_in_unicast_pkts untyped
interface_in_unicast_pkts{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Ethernet1",net_os="eos",region="lab",site="lab-site-01"} 21
# HELP interface_out_broadcast_pkts Telegraf collected metric
# TYPE interface_out_broadcast_pkts untyped
interface_out_broadcast_pkts{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Ethernet1",net_os="eos",region="lab",site="lab-site-01"} 0
# HELP interface_out_discards Telegraf collected metric
# TYPE interface_out_discards untyped
interface_out_discards{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Ethernet1",net_os="eos",region="lab",site="lab-site-01"} 0
# HELP interface_out_errors Telegraf collected metric
# TYPE interface_out_errors untyped
interface_out_errors{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Ethernet1",net_os="eos",region="lab",site="lab-site-01"} 0
# HELP interface_out_mac_control_frames Telegraf collected metric
# TYPE interface_out_mac_control_frames untyped
interface_out_mac_control_frames{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Ethernet1",net_os="eos",region="lab",site="lab-site-01"} 0
# HELP interface_out_mac_pause_frames Telegraf collected metric
# TYPE interface_out_mac_pause_frames untyped
interface_out_mac_pause_frames{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Ethernet1",net_os="eos",region="lab",site="lab-site-01"} 0
# HELP interface_out_multicast_pkts Telegraf collected metric
# TYPE interface_out_multicast_pkts untyped
interface_out_multicast_pkts{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Ethernet1",net_os="eos",region="lab",site="lab-site-01"} 0
# HELP interface_out_octets Telegraf collected metric
# TYPE interface_out_octets untyped
interface_out_octets{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Ethernet1",net_os="eos",region="lab",site="lab-site-01"} 0
# HELP interface_out_unicast_pkts Telegraf collected metric
# TYPE interface_out_unicast_pkts untyped
interface_out_unicast_pkts{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Ethernet1",net_os="eos",region="lab",site="lab-site-01"} 0

# HELP memory_available Telegraf collected metric
# TYPE memory_available untyped
memory_available{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Chassis",net_os="eos",region="lab",site="lab-site-01"} 1.6390119424e+10
# HELP memory_utilized Telegraf collected metric
# TYPE memory_utilized untyped
memory_utilized{collection_method="gnmi",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",name="Chassis",net_os="eos",region="lab",site="lab-site-01"} 7.414636544e+09

`[[inputs.execd]]`

# HELP bgp_sessions_prefixes_received Telegraf collected metric
# TYPE bgp_sessions_prefixes_received untyped
bgp_sessions_prefixes_received{collection_method="execd",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",local_as="65111",neighbor_address="10.1.2.2",net_os="eos",peer_as="65222",peer_router_id="10.17.17.2",peer_type="external",region="lab",router_id="10.17.17.1",routing_instance="default",session_state="established",site="lab-site-01"} 1
bgp_sessions_prefixes_received{collection_method="execd",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",local_as="65111",neighbor_address="10.1.7.2",net_os="eos",peer_as="65222",peer_router_id="0.0.0.0",peer_type="external",region="lab",router_id="10.17.17.1",routing_instance="default",session_state="active",site="lab-site-01"} 0
# HELP bgp_sessions_prefixes_sent Telegraf collected metric
# TYPE bgp_sessions_prefixes_sent untyped
bgp_sessions_prefixes_sent{collection_method="execd",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",local_as="65111",neighbor_address="10.1.2.2",net_os="eos",peer_as="65222",peer_router_id="10.17.17.2",peer_type="external",region="lab",router_id="10.17.17.1",routing_instance="default",session_state="established",site="lab-site-01"} 1
bgp_sessions_prefixes_sent{collection_method="execd",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",local_as="65111",neighbor_address="10.1.7.2",net_os="eos",peer_as="65222",peer_router_id="0.0.0.0",peer_type="external",region="lab",router_id="10.17.17.1",routing_instance="default",session_state="active",site="lab-site-01"} 0
# HELP bgp_sessions_session_state_code Telegraf collected metric
# TYPE bgp_sessions_session_state_code untyped
bgp_sessions_session_state_code{collection_method="execd",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",local_as="65111",neighbor_address="10.1.2.2",net_os="eos",peer_as="65222",peer_router_id="10.17.17.2",peer_type="external",region="lab",router_id="10.17.17.1",routing_instance="default",session_state="established",site="lab-site-01"} 6
bgp_sessions_session_state_code{collection_method="execd",device="ceos-01",device_platform="arista",device_role="router",environment="dev",host="telegraf-01",local_as="65111",neighbor_address="10.1.7.2",net_os="eos",peer_as="65222",peer_router_id="0.0.0.0",peer_type="external",region="lab",router_id="10.17.17.1",routing_instance="default",session_state="active",site="lab-site-01"} 3

Conclusion

The best parts of the Telemetry Stack! series are yet to come, so stay tuned! For any question you may have, feel free to join our Slack community.

-Nikos

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Conclusion

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Contents

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Blog Detail

Differentiation from Other Libraries

Installation

Getting Connected

Sending Commands

Command Output Parsing

TextFSM

TTP

Genie

Next Steps

Conclusion

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Contents

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Blog Detail

Introduction to the Telemetry Stack!

Telegraf

Prometheus

Grafana

Alertmanager

Capturing Metrics and Data Using Telegraf

[[inputs.snmp]]

[[inputs.gnmi]]

[[inputs.execd]]

Collected Data

[[inputs.snmp]]

[[inputs.gnmi]]

[[inputs.execd]]

Conclusion

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`[[inputs.snmp]]`

`[[inputs.gnmi]]`

`[[inputs.execd]]`

`[[inputs.snmp]]`

`[[inputs.gnmi]]`

`[[inputs.execd]]`