experience ascent
The Topology View feature transforms how you interact with ingested data. It’s designed as a logical topology browser, enabling you to group and work with applications and data seamlessly. This intuitive approach means that related applications and data are easily accessible in one place.
Apica’s distributed tracing view facilitates trace searches using attribute-based criteria. Users input specific attributes and values, prompting the system to retrieve matching traces and spans.
1. Criteria Input: Define attributes and their corresponding values for the search.
2. Systematic Search: Apica’s system conducts a thorough scan to find matching traces and spans.
3. Visualization of Results: The interface displays the matching traces, allowing for clear and organized data analysis.
Key Advantages
Targeted Search: Enables precise filtering based on specific data attributes.
Efficiency: Streamlines the search process, reducing time spent on data retrieval.
Clear Data Presentation: Facilitates easy interpretation and analysis of complex trace data. “
Users have the flexibility to sift through logs by selecting their desired time range. Choose from a predefined set of relative time options or use dynamic relative time range selector for sepcific log searches.
Build complex expressions in a search query for searching logs. Advance Query supports the use of complex expressions in the search query for log search.
The favorites feature allows you to mark your search queries for quick and easy access in the future. Simply mark a query as a favorite, and you’ll be able to retrieve it swiftly the next time you need it.
The Import Dashboard feature lets you quickly leverage pre-defined dashboards tailored for common use cases, enabling efficient monitoring of your application and infrastructure. Avoid the hassle of building complex dashboards from scratch and gain insights faster with just a few clicks.
Detecting anomalies in metrics like the network-receive-byte count is simplified through machine learning techniques applied to time-series data. Here’s a streamlined process that anyone can follow, regardless of technical expertise:
Start with Pre-Formed Time-Series Data: Choose your metric data set for analysis.
Generate Data with a Query: Use a specific query to produce the time-series data you’re interested in.
Visualize with a Chart: View the generated data on a plotted time-series chart, which will display two sets: the original data (e.g., Network-total-received bytes) and the detected anomalies.
Adjust Anomaly Detection: Users have the option to fine-tune the sensitivity of anomaly detection to achieve the most accurate results.
Initially, set the anomaly detection strength to 40% and observe the highlighted anomalies.
Interpreting security event logs can often be a challenging task due to their complex nature. However, leveraging Gen-AI technology can significantly aid in understanding these logs more clearly.
By integrating Gen-AI into your log event explorer, you can streamline the process of analyzing and interpreting security logs. Here’s how to make the most of Gen-AI for security log analysis:
OSSEC stands as the most popular Host-based Intrusion Detection System (HIDS) for meticulous security monitoring and capturing compliance evidence. The Apica Ascent Platform fully supports OSSEC, along with its enhanced capabilities, ensuring a robust security framework for your organization.
Our tutorial showcases the simplicity and speed of deploying OSSEC within Apica.
Follow these straightforward steps:
Setting up the enhanced OSSEC server on Apica for your end devices is straightforward, ensuring a fortified security posture and streamlined compliance monitoring.”
Logs Live Tail streamlines troubleshooting by offering a real-time stream of new log events as they arrive. This feature enables you to swiftly detect and address issues by viewing, filtering, and highlighting logs almost instantaneously.
To use Live Tail, navigate to the explore view, select your desired namespace/application, and start tailing logs live. You also have the option to pause the live stream and download the logs you’ve tailed for further analysis or record-keeping.
The TimeZone setting gives users the capability to set the timeZone based on their preference. Choose the prefered timezone from the dropdown meanu or search for the relavant keyword.
Users can enable SAML login from the settings for ease-of-access in logging in to the application.
Users can configure emails to forward alerts and send email invites by anvigating to the mail tab in settings and configuring the details.
Filter the namespace or application based on the keyword search, or select multiple namespaces to filter out your data.
In Apica Ascent, rules and rule packs play a pivotal role in data management, allowing users to effectively manage the cost and flow of their data. Here’s a
Creating Rules: Users can create a new rule within a specific namespace and application flow. This is done by hovering over any log line and selecting “”Create rule.”” Once established, the rule applies to every log incoming in that flow.
Filter Rule: It filters events based on certain criteria, controlling the volume of data stored or processed. For example, you can create a filter rule to drop all log lines containing DEBUG or INFO severity levels.
Extract Rule: This rule helps extract unstructured data from log lines using re2 RegEx pattern expressions. It evaluates incoming log lines and extracts specified fields.
SIEM (Log-to-Metric) Rule: Converts incoming log data into real-time timeseries metrics. It’s used for visualizing log data, plotting distributions, creating custom indexes, and alerting for events like user login failures or load-balancer status codes.
Rewrite Rule: Used for redacting or replacing sensitive data in compliance with data security regulations. It utilizes RegEx to match and mask patterns in incoming data.
Forward Rule: Applied when routing logs to downstream destinations. These rules can be used to selectively forward data, ensuring compliance and reducing data volume.
Rule Packs: Rule Packs are collections of various types of rules (FILTER, EXTRACT, SIEM, REWRITE, FORWARD). Users can access built-in rule packs or create new ones. Each pack can be edited to suit specific needs and activated or deactivated as required.
Managing Rules: Users can view, edit, and delete rules via the rules list page, which offers filters and status checks. The detailed view of each rule is accessible, providing options for modification or removal.
Apica Ascent’s filter rules are key for efficient data management, allowing users to control data costs and streamline data flow. These rules enable you to specify criteria that log data must meet to be collected, thus filtering out irrelevant data. This process not only helps manage storage costs by reducing the amount of data stored but also enhances data analysis efficiency by focusing on relevant information.
Apica Ascent’s extract rules are designed to efficiently manage data costs and flow by transforming unstructured log data into structured formats. This process allows for precise data analysis and forwarding to targeted destinations through forward rules.
Extract rules identify and extract relevant information from unstructured data based on predefined patterns, converting it into a structured format ready for further processing.
Extract rules simplify the management of unstructured data, making it easier to analyze and process, leading to more efficient data workflows and cost savings.
A data pipeline orchestrates the flow of data through a predefined series of steps or processes. It’s designed for systematic and efficient data movement and transformation, incorporating various operations such as filtering and rule application to manage the data stream.
Apply robust operations on incoming logs with the help of the CODE Rule.
Code Rule allows you to apply JavaScript Code on logs, giving you access to extract information, obfuscate credentials, and even make HTTP requests.
Rewrite/mask confidential contents in a message with the Rewrite rule. The rule takes in a regex to match a substring in the message, and then replaces it with the given rewrite string.
Steps to onboard users from ASM to ASM+:
Click on the ASM+ button to go to the new ASM+ Page.
The ASM+ Portal combines observability and synthetic monitoring into one powerful platform for comprehensive performance insights.
Creating a browser check is an essential and widely-used method for tracking user interactions and experiences on your platform. Here’s how to efficiently set one up:
Steps for Configuring URL Checks:
Use a swift, three-click process to identify the underlying cause of a failure in a synthetic check. Watch as we pinpoint the application error responsible for disrupting a Synthetic script’s performance.
