Datadog python logging. -e DD_LOGS_CONFIG_CONTAINER_COLLECT_ALL=true.

statsd modules. MachineName, . Extensions. To enable instrumentation of pytest tests, add the --ddtrace option when running pytest, specifying the name of the service or library under test in the DD_SERVICE environment variable, and the environment where tests are being run (for example, local when running tests on a developer workstation, or ci when Now, let's say that I want to send logs from it to Datadog. If logs are in JSON format, Datadog automatically parses the log messages to extract log attributes. apiKey: "REPLACE - DataDog API Key", host: Environment. Get started quickly with built-in support for Python frameworks like Django and Flask. This optional feature is enabled by setting the DD_PROFILING_ENABLED environment variable to true. Datadog のインテグレーションとログ収集は連携しています。インテグレーションのデフォルト構成ファイルを使用すると、Datadog で専用のプロセッサー、パース、およびファセットを有効にできます。インテグレーションでログ収集を開始するには: Agent Configuration. Datadog's Continuous Profiler is now available in beta for Python in version 4. If you are using the Forwarder Lambda function to collect traces and logs, dd. Use logging The module can be downloaded from PyPI and installed in one step with easy_install: >>> sudo easy_install dogapi. The Agent looks for log instructions in configuration files. pytest. Log in to your Datadog account and select Integrations > APIs to get your API key. Sensitive Data Scanner is a stream-based, pattern matching service that you can use to identify, tag, and optionally redact or hash sensitive data. # service : (mandatory) name of the service owning the log. Resolve detected Python problems faster with distributed request traces, logs, and infrastructure metrics all The commands related to log collection are: -e DD_LOGS_ENABLED=true. The API uses resource-oriented URLs to call the API, uses status codes to indicate the success or failure of requests, returns JSON from all requests, and uses standard HTTP response codes. Logs are automatically sent to the console for Python 3 applications. read. The Python standard library log records contains a large set of attributes, however only a few are included in Powertools for AWS Lambda (Python) Logger log record by default. The Datadog Agent has two ways to collect logs: from Kubernetes log files, or from the Docker socket. The simplest way is to use init_logging() which will log to stdout. mymodule. For instance, you can correlate Azure Functions traces with metrics collected from your underlying App Service plan at the time of the trace Navigate to the Generate Metrics page. Override the modules patched for this application execution. Aug 29, 2018 · logging_automation. When it occurs, the Datadog Agent outputs a log containing Restarting reader after a read timeout for a given container every 30 seconds and stops sending logs from that container while it is actually logging messages. When there are many containers in the same Mar 19, 2024 · The Datadog Python Library is a collection of tools suitable for inclusion in existing Python projects or for the development of standalone scripts. Get metrics from Azure Functions to: Visualize your function performance and utilization. You can now move on to the next attribute, the severity. Feb 17, 2022 · I'm not sure if I got the datadog settings right, so I'm including it here. Aug 7, 2019 · I am writing a Airflow DAG and having some problems with a function. x to 1. com/nG5SXezJ----- Connect With Me -----Website : https://soumilshah. getLogger(__name__) logger. This enables you to cost-effectively collect, process, archive, explore, and monitor all of your logs without limitations, also known as Logging without Limits*. Configuration options To fix the error, give the Datadog Agent user read and execute permissions to the log file and subdirectories. Scenario 3: ddtrace version 1. Before we jump into the hands-on part, let’s first understand some common logging challenges based on the example above. Use a log shipper. During the beta period, profiling is available at no additional cost. Installation. Monitor Python applications alongside data from 750+ other turnkey integrations. Run the Agent’s status subcommand and look for java under the Checks section to confirm logs are successfully submitted to Datadog. The following components are involved in sending APM data to Datadog: Traces (JSON data type) and Tracing Application Metrics are generated from the application and sent to the Datadog Agent before traveling to the backend. For information on configuring Datadog integrations, see Integrations. Initialize and configure Datadog. I've tried with both DD_LOGS_INJECTION=true and The Python integration allows you to collect and monitor your Python application logs, traces, and custom metrics. Python monitoring provides code-level visibility into the health and performance of your services, allowing you to quickly troubleshoot any issue—whether it's related to coroutines, asynchronous tasks, or runtime metrics. Sep 21, 2022 · This is likely due to the Python standard logging module defaulting to use stderr as its output stream. Read more about compatibility information. If this is the case, Datadog may already support the technology you need. See the dedicated documentation for instrumenting your Python application to send its traces to Datadog. start_profiler () # Should be as early as possible, eg before other imports, to ensure everything is profiled # Alternatively, for manual instrumentation, # create a new profiler The simplest way to enable logging to DataDog is to use the log_error_events helper, which will cause all logging. Or with pip: >>> sudo pip install dogapi. Select Grok Parser for the processor type. It provides an abstraction on top of Datadog's raw HTTP interface and the Agent's DogStatsD metrics aggregation server, to interact with Datadog and efficiently report events and metrics. This page also describes how to set up custom metrics, logging, and tracing for your Lambda functions. js, . You can also create metrics from an Analytics search by selecting the “Generate new metric” option from the Export menu. Use the Datadog API to access the Datadog platform programmatically. Installation pip install datadog-logger Usage. After you install and configure your Datadog Agent, the next step is to add the tracing library directly in the application to instrument it. How can I set such variables in PYthon Logging library? Sep 6, 2019 · Handling multi-line logs. If you want finner control then you can use DatadogFormatter directly. Host Configure Datadog Agent Airflow integration. code https://pastebin. The Datadog trace and log views are connected using the Datadog trace ID. api. Enable Agentless logging. Jun 4, 2021 · 2. You can include any of these logging attributes as key value arguments ( kwargs) when instantiating Logger or LambdaPowertoolsFormatter. Troubleshoot Python queries impacting performance for databases like MongoDB or Elasticsearch. # - type : file (mandatory) type of log input source (tcp / udp / file) # port / path : (mandatory) Set port if type is tcp or udp. Write out JSON formatted logs in the format and with the attributes that Datadog expects. In the example, there is a logs' format with custom variables that contain a dot . py starting on line 83: api_key={'cookieAuth': 'abc123'} api_key_prefix={'cookieAuth': 'JSESSIONID'} My guess is using the example for v1 for authentication but changing v1 to v2 would work Jun 20, 2024 · Datadog appears to only log uncaught exceptions, but there are certain caught exceptions that I would like to log as exception as well. Select the Generate Metrics tab. stderr will be used. The Datadog Lambda Extension introduces a small amount of overhead to your Lambda function’s cold starts (that is, the higher init duration), as the Extension needs to initialize. basicConfig() or use DD_CALL_BASIC_CONFIG=true. You may notice an increase of your Lambda Apr 16, 2019 · Datadog automatically brings together all the logs for a given request and links them seamlessly to tracing data from that same request. With distributed tracing, out-of-the-box dashboards, and seamless correlation with other telemetry data, Datadog APM helps ensure the best Datadog Log Management, also referred to as Datadog logs or logging, removes these limitations by decoupling log ingestion from indexing. Enable this integration to begin collecting CloudWatch metrics. To send your C# logs to Datadog, use one of the following approaches: Log to a file and then tail that file with your Datadog Agent. AddLogging(loggingBuilder =>. 2. AWS Lambda is a compute service that runs code in response to events and automatically manages the compute resources required by that code. pip install datadog-log. g. Maximum array size if sending multiple logs in an array: 1000 entries. Any help is highly appreciated, I am looking for a solution using Option 1. More than 10 containers are used on each node. Forward metrics, traces, and logs from AWS Lambda Datadog DJM is billed per host, per hour. To use the examples below, replace <DATADOG_API_KEY> and <DATADOG_APP_KEY> with your Datadog API key and your Datadog application key, respectively. Tagging. Classic Logging Challenges. Build and debug locally without additional setup, deploy and operate at scale in the cloud, and integrate services using triggers and bindings. Apr 13, 2023 · Native Python logger. Service checks. This section covers information on configuring your Datadog Agents. Trace collection. You first need to escape the pipe (special characters need to be escaped) and then match the word: And then you can keep on until you extract all the desired attributes from this log. Any log exceeding 1MB is accepted and truncated by Datadog: For a single log request, the API Tags are a way of adding dimensions to Datadog telemetries so they can be filtered, aggregated, and compared in Datadog visualizations. AddSerilog(. Let's dive into the practicalities of integrating Datadog into Python code. What’s an integration? See Introduction to Integrations. That way any log generated by your Jul 3, 2018 · To start instrumenting your application code for logging, you’ll need to import a Python logging library. You may want to develop on Datadog if there is data you want to see in the product that you are not seeing. Feb 2, 2024 · A Python logging. using ddtrace import ddtrace. yaml file, in the conf. Section 3: Instrumenting Your Code 3. Click +New Metric. Datadog Log Management unifies logs, metrics, and traces in a single view, giving you rich context for analyzing log data. Jul 1, 2022 · The Datadog App Service extension expands on our Azure App Service integration, enabling you to correlate Azure Functions trace data with metrics, traces, and logs from across your Azure-hosted resources. 4+) log4net; NLog; Microsoft. Product Brief: Logging without Limits™ Learn to cost-effectively collect, process, and archive logs. 28. You can easily visualize all of this data with Datadog’s out-of-the-box integration and enhanced metrics Correlate Logs and Traces. Set path if type is file. This could lead to read timeouts when the Datadog Agent is gathering the containers’ logs from the Docker daemon. Scenario 4: ddtrace version 0. pytest-benchmark. Datadog simplifies log monitoring by letting you ingest, analyze, and archive 100 percent of logs across your cloud environment. Setup. Learn more about the next major version of Datadog Agent 7 and some new tools for migrating your custom Python Python logging formats: How to collect and centralize Python logs Learn how to use these Python logging best practices to debug and optimize your applications. Datadog APM can even auto-instrument some libraries, like aiohttp and aiopg. environ[] method Contribute to DataDog/datadog-lambda-python development by creating an account on GitHub. com title: getting started with datadog python logging: a comprehensive tutorialdatadog is a popular Aug 30, 2021 · Visualize your AWS Lambda metrics. 1 Pythonic Enchantments: Integrating Datadog in Python. Monitor real user data in order to optimize your web performance and provide exceptional user experiences. Ensure that log collection is configured in the Datadog Agent and that the Logs Agent configuration for the specified files to tail is set to source: csharp so If you haven’t already, create a Datadog account. In either case, we generally recommend that you log to a file in your environment. MyHandler (for a class defined in package mypackage and module mymodule, where mypackage is available on the Python import path). NET Tracer supports the following logging libraries: Serilog (v1. Datadog. Use of the Logs Search API requires an API key and an application key. Identify critical issues quickly with real-time service maps, AI-powered synthetic monitors, and alerts on latency, exceptions, code-level errors, log issues, and more. See across all your systems, apps, and services. new LoggerConfiguration() . Datadog’s Python DD Trace API allows you to specify spans within your code using annotations or code. My python. This page details setup examples for the Serilog, NLog, log4net, and Microsoft. -e DD_LOGS_CONFIG_CONTAINER_COLLECT_ALL=true. Use the Serilog sink. All of the devices in your network, your cloud services, and your applications emit logs that may The . warning("Dummy log") but this is not working. If stream is specified, the instance will use it for logging output; otherwise, sys. We will go over two primary methods for collecting and processing multi-line logs in a way that aggregates them as single events: Log to JSON format. Datadog is continuously optimizing the Lambda extension performance and recommend always using the latest release. The Datadog Forwarder is an AWS Lambda function that ships logs from AWS to Datadog, specifically: Forward CloudWatch, ELB, S3, CloudTrail, VPC, SNS, and CloudFront logs to Datadog. Jul 4, 2024 · Logging setup for FastAPI. Enables log collection when set to true. x. Adds a log configuration that enables log collection for all containers. I've been trying to log them manually by adding them to a spa Feb 19, 2023 · We have created a simple python file that contains all the logging information called logging_dd. This uses an average host count per hour, by sampling the number of unique hosts instrumented every five minutes and taking an average of those samples. With Log Management, you can analyze and explore data in the Log Explorer, connect Tracing and Metrics to correlate valuable data across Datadog, and use ingested logs for Datadog Cloud SIEM. Limits per HTTP request are: Maximum content size per payload (uncompressed): 5MB. The Datadog Python log documentation gives a detailed example of how to use a library to send Python logs to your Datadog account. Using tags enables you to observe aggregate performance across several hosts and (optionally) narrow the set further based on specific elements. Example: Suppose we observe: 1:00-1:05 pm: 100 unique DJM hosts. Add custom instrumentation to the Python application. Finally, a logging interface that is just slightly more syntax than print to do mostly the right thing, and all that fancy stuff like log rotation is easy to figure out. 1. Usage. 62. Install it on your system by following the step-by-step instructions tailored to your environment. To start collecting logs from your AWS services: Set up the Datadog Forwarder Lambda function in your AWS account. herokuapp. 0 and layer version 62 and above. First, import a Python logging library. I am trying to debug by printing data to stdout and using the logging library. Different troubleshooting information can be collected at each section of the pipeline. . Datadog Custom Logger. For example, the log may look like: WARNING: John disconnected on 09/26/2017. dashboards_api import DashboardsApi async def main(): configuration = Configuration() async with C# Log Collection. Then, you can use Structlog loggers or standard logging loggers, and they both will be processed by the Structlog pipeline (see the hello() endpoint for reference). Click Create API key or Create Client Token. I thought that the simples way to do it would be via Datadog's agent, e. comGithu Restart the Agent. x Python Application Monitoring. Datadog will automatically start collecting the key Lambda metrics discussed in Part 1, such as invocations, duration, and errors, and generate real-time enhanced metrics for your Lambda functions. ) – Proxy to use to connect to Datadog API. Setup Metric collection. For Python and Node. この問題に対処するため、Datadog はロギング時に JSON フォーマッター Create the rule: So you know the date is correctly parsed. To begin tracing applications written in Python, install the Datadog Tracing library, ddtrace, using pip: Overview. py install. In this section, we’ll step through a simple example to demonstrate. See full list on github. Logging without Limits* enables a streamlined Datadog Logging without Limits* decouples log ingestion and indexing. Configure a logging source. load(event_log_path) Feb 9, 2021 · Option 3: using Serilog but, my organization does not want to use third party logging framework, we have our own logging framework. Free. For information on remotely configuring Datadog components, see Remote Configuration. 1:05-1:10 pm: 300 unique DJM hosts. i. 6) Configure log collection. Docs > Agent > Agent Configuration. Configuring the Python Tracing Library. Logging (added in v1. With these fields you can find the exact logs associated with a specific service and version, or all logs correlated to an observed trace. Automatic instrumentation is convenient, but sometimes you want more fine-grained spans. Add a new log-based metric. Easily rehydrate old logs for audits or historical analysis and seamlessly correlate logs with related traces and metrics for greater context when troubleshooting. getenv("SERVICE_NAME"), logger_name=os. To install from source, download a distribution and run: >>> sudo python setup. Use the word() matcher to extract the status and pass it into a custom log_status attribute. Jul 24, 2022 · Now I'm trying to adopt the official example from DataDog docs. Choose which logs to index and retain, or archive, and manage settings and controls at a top-level from the log configuration page at Logs > Pipelines. Python のログは、トレースバックのために扱いが複雑になることがあります。. js serverless applications, Datadog recommends you install Datadog’s tracing libraries. The easiest way to get your custom application metrics into Datadog is to send them to DogStatsD, a metrics aggregation service bundled with the Datadog Agent. Logging without Limits™ lets you cost-effectively Datadog-log. Note: See PCI DSS Compliance for information on setting up a PCI-compliant Datadog organization. The lifecycle of a log within Datadog begins at ingestion from a logging API Reference. Contribute to DataDog/dd-trace-py development by creating an account on GitHub. See the dedicated documentation for collecting Python custom metrics with DogStatsD. Whether you’re troubleshooting issues, optimizing performance, or investigating security threats, Logging without Limits™ provides a cost-effective, scalable approach to centralized log management, so Azure Functions is an event-driven serverless compute platform that can also solve complex orchestration problems. Lambda Profiling Beta. The Docker API is optimized to get logs from one container at a time. yml. Maximum size for a single log: 1MB. In events I have all events for that table, and I need just events for last Delta Live Table process. It's the same when I run it locally, but maybe not the same loss rate. com Nov 28, 2022 · Further Reading. The Datadog API is an HTTP REST API. The Datadog Agent’s Gunicorn check is included in the Datadog Agent package, so you don’t need to install anything else on your Gunicorn servers. dashboards_api import DashboardsApi async def main(): configuration = Configuration() async with Dec 21, 2018 · 1. import asyncio from datadog_api_client import Configuration, AsyncApiClient from datadog_api_client. If you want to use DataDog for logging from Azure Function of App Service you can use Serilog and DataDog Sink to the log files: services. Linux. To add a Datadog API key or client token: Click the New Key or New Client Token button, depending on which you’re creating. For container installations, see Container Monitoring. logger = logging. Enter a name for your key or token. DatadogLogs(. NET, PHP, and many associated frameworks, you can start correlating logs and request traces without touching your application code. The user who created the application key must have the appropriate permission to access the data. ERROR and higher messages to be sent to DataDog: Nov 15, 2023 · The Datadog Agent is your trusty companion in this adventure. Sensitive Data Scanner is available in Aug 23, 2021 · Datadog’s Logging without Limits™ eliminates this tradeoff between cost and visibility by enabling you to ingest all of your logs and dynamically decide later on which ones to index. The Datadog trace and log views are connected using the AWS Lambda request ID. basicConfig () log_error_events ( tags= [ "tag1:value", "tag2:value" ], mentions Navigate to Logs Pipelines and click on the pipeline processing the logs. event_log = spark. Events. 7, you need to manually start a new profiler in your child process: # For ddtrace-run users, call this in your child process ddtrace . See the table of commonly requested technologies to find the product or integration This Lambda—which triggers on S3 Buckets, CloudWatch log groups, and EventBridge events—forwards logs to Datadog. See init_logging for example usage. For instance, when you’re investigating the cause of high latency in your application, you can use Log Patterns to help you identify noisy log types that May 20, 2022 · For getting metrics from Delta Live Tables, I use events and Delta Live History. Jul 1, 2024 · To make async support available, you need to install the extra async qualifiers during installation: pip install datadog-api-client[async]. Download to learn more Automatically instrument applications for popular Python frameworks. py). Use the Log Explorer to view and troubleshoot your logs. Delay import of logging initialization code. Logging logging libraries, for each of the above approaches. Overview. in their names. Use Datadog Log Management to query, analyze, monitor, and visualize log data from all of your logs sources. Key names must be unique across your Thus, you could use either WatchedFileHandler (relative to the logging module) or mypackage. api client requires to run datadog initialize method first. Handler for sending log messages to DataDog as Events in the Events Explorer. bonus: README is a nice tour of features with examples. To route logs to the console, for Python 2 or Python 3 applications, configure logging. You can either set them up by configuring the system environment variables or using python's os. These two log lines describe what is happening during a request. This logging setup configures Structlog to output pretty logs in development, and JSON log lines in production. Input a query to filter the log stream: The query syntax is the same as for the Log Explorer Search. by @purple4reina in #468; Datadog Python APM Client. patch_all() import logging. Configure the Airflow check included in the Datadog Agent package to collect health metrics and service checks. profiling . d/conf. Below is a Introduction to Log Management. WriteTo. api is a Python client library for Datadog’s HTTP API. After you set up the tracing library with your code and configure the Agent to collect APM data, optionally configure the tracing library as desired, including setting up Unified Service Tagging. v1. The simplest way to enable logging to DataDog is to use the log_error_events helper, which will cause all logging. Troubleshoot Python App Performance Issues Faster with Datadog APM. From the StreamHandler constructor documentation. With auto-instrumentation for Java, Python, Ruby, Go, Node. To start tracing your asynchronous Python applications, you simply need to configure the tracer to use the correct context provider, depending on the async framework or library you’re using. With this capability, your security and compliance teams can introduce a line of defense in preventing sensitive data from leaking outside your organization. If you use virtualenv you do not need to use sudo. In summary, tagging is a method to observe aggregate data points. See More than 750 built-in integrations. auto . To emit custom metrics with the Datadog Lambda Layer, we first add the ARN to the Lambda function in AWS console: arn:aws:lambda:<AWS_REGION>:464622532012:layer:Datadog-<RUNTIME>:<VERSION>. Set up request id tracking (in front) and logging middlewares (at the end): Configure LOGGERS in your Django settings file: If you would like to whitelist your projects for passing extra arguments to the json log record, please set the following regular expression: Add Celery logger configuration and request_id tracking decorator In Python < 3. a logging API that fits in my brain. 2, a new means of configuring logging has been introduced, using dictionaries to hold configuration Jun 25, 2024 · I would instantiate the log this way: logger = init_datadog_logger(service_name=os. Click Add Processor. A Python monitoring solution can also continuously profile your code and seamlessly Enterprise-Ready. Ruby. Sep 18, 2017 · Tracing awaits. Your org must have at least one API key and at most 50 API keys. d/ folder at the root of your Agent’s configuration directory, to start collecting your Airflow service checks. I went through the Microsoft articles, Datadog documentation but, no luck. e. ⚠️ Make sure to setup these 2 environment variables before using this package. Datadog Real User Monitoring (RUM) provides deep insight into your application’s frontend performance. api and Datadog. The following steps walk you through adding annotations to the code to trace some sample methods. Search log data at any scale, investigate and resolve incidents, and understand your systems. DogStatsD implements the StatsD protocol and adds a few Datadog-specific extensions: Histogram metric type. This has several benefits over other logging methods. Jan 5, 2019 · Brian #1: loguru: Python logging made (stupidly) simple. However, we could improve the notation of the retries, add more context and make the log lines more readable. unittest. Datadog recommends using Kubernetes log files when: Docker is not the runtime, or. This can be done by editing the url within the airflow. Default: false Enable debug logging in the tracer. proxies ( dictionary mapping protocol to the URL of the proxy. getenv("SERVICE_NAME")) However from those 2500 logs, maybe only 2100-2200 make it in at any one point. Returns a new instance of the StreamHandler class. Datadog Application Performance Monitoring (APM) provides deep visibility into your applications, enabling you to identify performance bottlenecks, troubleshoot issues, and optimize your services. This is the only v2 authentication example I found on how to use Configuration in the github repo source code for datadog_api_client / v2 / configuration. The correlation between Datadog APM and Datadog Log Management is improved by the injection of trace IDs, span IDs, env, service, and version as attributes in your logs. トレースバックは、ログを複数行に分割する原因となり、元のログイベントとの関連付けが困難になります。. Windows (cmd) Windows (PowerShell) Run the namei command to obtain more information about the file permissions: > namei -m /path/to/log/file. All AI/ML ALERTING AUTOMATION AWS AZURE CACHING CLOUD COLLABORATION COMPLIANCE CONFIGURATION & DEPLOYMENT CONTAINERS COST MANAGEMENT DATA STORES DEVELOPER TOOLS EVENT MANAGEMENT GOOGLE CLOUD INCIDENTS Audit logging is the process of documenting activity within the software systems used across your organization. The Gunicorn check requires your Gunicorn app’s Python environment to have the setproctitle package; without it, the Datadog Agent reports that it cannot find a gunicorn master process (and To make async support available, you need to install the extra async qualifiers during installation: pip install datadog-api-client[async]. loggingBuilder. (To make use of these features, make sure that you’re Troubleshooting pipeline. The primary package we are using is the Datadog API client Quick start. In the following example, the Agent user does not have execute permissions on the The Developers section contains reference materials for developing on Datadog. Logging. ddtrace. Send your logs to your Datadog platform over HTTP. Instantly Download or Run the code at https://codegive. To enable debug mode: DD_TRACE_DEBUG=true. My example DAG is: from datetime import timed Add an API key or client token. In Python 3. 0. py in the repo (utils/logging_dd. Forward S3 events to Datadog. trace_id is automatically injected into logs (enabled by the environment variable DD_LOGS_INJECTION). ERROR and higher messages to be sent to DataDog: # Note, a normal STDOUT handler will not be configured if this is not # called first logging. The Datadog Lambda Library and tracing libraries for Ruby support: Automatic correlation of Lambda logs and traces with trace ID and tag Datadog. First, update the Datadog Lambda function. Enable logging for your AWS service (most AWS services can log to a S3 bucket or CloudWatch Log Group). Looking to trace through serverless resources not listed above? Open a feature request. py – The Python script to create a new account and deploy the CloudFormation template; A Datadog account—if you don’t have one already, please create a new Datadog account here; Initial Setup. Forward Kinesis data stream events to Datadog (only CloudWatch logs are supported). Correlate synthetic tests, backend metrics, traces, and logs in a single place to quickly identify and troubleshoot performance issues Sep 20, 2017 · response returns the requested string or hash, if the request is successful, along with an HTTP status code. format('delta'). Audit logs record the occurrence of an event, the time at which it occurred, the responsible user or service, and the impacted entity. wf er ef no hy xx xn ks ov en