cybersecurity

How to Avoid Common Cloud Security Mistakes and Manage Cloud Security Risk

cloud monitoing, cybersecurity, shared fate

Cloud computing has become a dominant trend in the IT industry, offering many benefits such as scalability, flexibility, cost-efficiency, and innovation. However, cloud computing also introduces new challenges and risks for security and compliance. According to a recent report by LogicMonitor, 87% of global IT decision-makers agree that cloud security is a top priority for their organization, but only 29% have complete confidence in their cloud security posture.

Moreover, the report reveals that 66% of respondents have experienced a cloud-related security breach in the past year, and 95% expect more cloud-related security incidents in the future.

Therefore, enterprises need to adopt best practices and strategies to avoid common cloud security mistakes and manage cloud risk effectively.

We are going to review now some of the most common cloud security mistakes made by enterprises, and how to prevent or mitigate them. We will also discuss how to adopt a shared fate approach to manage cloud risk, which is a concept proposed by Google Cloud Security.

Common Cloud Security Mistakes

Some of the most common cloud security mistakes made by enterprises are:

• Lack of visibility and control: Many enterprises do not have a clear understanding of their cloud assets, configurations, dependencies, and vulnerabilities. They also do not have adequate tools and processes to monitor, audit, and enforce their cloud security policies and standards. This can lead to misconfigurations, unauthorized access, data leakage, compliance violations, and other security issues.

• Lack of shared responsibility: Many enterprises do not fully comprehend the shared responsibility model of cloud security, which defines the roles and responsibilities of the cloud provider and the cloud customer. They either assume that the cloud provider is responsible for all aspects of cloud security, or that they are responsible for none. This can result in gaps or overlaps in cloud security coverage, as well as confusion and conflicts in case of a security incident.

• Lack of skills and expertise: Many enterprises do not have enough skilled and experienced staff to handle the complexity and diversity of cloud security challenges. They also do not invest enough in training and education to keep up with the evolving cloud security landscape. This can result in human errors, poor decisions, delayed responses, and missed opportunities.

• Lack of automation and integration: Many enterprises rely on manual processes and siloed tools to manage their cloud security operations. They also do not leverage the automation and integration capabilities offered by the cloud platform and third-party solutions. This can result in inefficiency, inconsistency, redundancy, and scalability issues.

• Lack of governance and compliance: Many enterprises do not have a clear and consistent framework for governing their cloud security strategy, objectives, policies, procedures, roles, and metrics. They also do not have a systematic approach to ensuring compliance with internal and external regulations and standards. This can result in misalignment, confusion, duplication, and non-compliance.

How to Prevent or Mitigate Common Cloud Security Mistakes

To prevent or mitigate these common cloud security mistakes, enterprises should adopt the following best practices and strategies:

• Gain visibility and control: Enterprises should use tools and techniques such as asset inventory, configuration management, dependency mapping, vulnerability scanning, threat detection, incident response, and forensics to gain visibility and control over their cloud environment. They should also implement policies and standards for securing their cloud resources, such as encryption, authentication, authorization, logging, backup, recovery, etc.

• Understand shared responsibility: Enterprises should understand the shared responsibility model of cloud security for each cloud service model (IaaS, PaaS, SaaS) and each cloud provider they use. They should also communicate and collaborate with their cloud providers to clarify their respective roles and responsibilities, as well as their expectations and obligations. They should also review their contracts and service level agreements (SLAs) with their cloud providers to ensure they cover their security requirements.

• Build skills and expertise: Enterprises should hire or train staff who have the necessary skills and expertise to manage their cloud security challenges. They should also provide continuous learning opportunities for their staff to update their knowledge and skills on the latest cloud security trends and technologies. They should also seek external help from experts or consultants when needed.

• Leverage automation and integration: Enterprises should use automation tools such as scripts.

Could Shared Fate be the Best Approach for Cloud Security?

cloud monitoing, cybersecurity, shared fate

Cloud security is a critical concern for any organization that uses cloud services to run their applications and store their data. Cloud security involves protecting the confidentiality, integrity, and availability of the cloud resources and data from various threats and risks. However, cloud security is not a simple or straightforward task, as it involves many challenges and complexities.

One of the challenges of cloud security is understanding and applying the shared responsibility model, which defines the roles and responsibilities of the cloud provider and the cloud customer. Depending on the type of cloud service they use (IaaS, PaaS, SaaS), the customer may have more or less control and responsibility over their cloud security. However, the shared responsibility model can sometimes create confusion or gaps in cloud security coverage, as different cloud services have different configuration options and security controls.

Another challenge of cloud security is managing the trust and collaboration between the cloud provider and the customer. The cloud provider and the customer may have different goals, expectations, and incentives when it comes to cloud security. The cloud provider may want to maximize their profit and reputation, while the customer may want to minimize their cost and risk. The cloud provider and the customer may also have different levels of expertise, visibility, and access to the cloud environment. This can result in miscommunication, misunderstanding, or conflict in case of a security incident.

To overcome these challenges and achieve better security outcomes in the cloud, a new approach is needed: shared fate. Shared fate is a concept proposed by Google Cloud Security, which aims to improve the security outcomes for cloud customers and providers. Shared fate is based on the idea that both parties have a common interest and stake in securing the cloud environment, and that they should work together as partners rather than adversaries.

Shared fate goes beyond the traditional shared responsibility model, which defines the roles and responsibilities of the cloud provider and the customer based on the type of cloud service they use. While shared responsibility is still important, it can sometimes create confusion or gaps in cloud security coverage, as different cloud services have different configuration options and security controls.

Shared fate sees the cloud provider accepting the reality of where shared responsibility breaks down and steps up to close the gaps. The cloud provider does this by offering secure-by-default infrastructure, security foundations, and secure blueprints that help customers deploy their workloads in a secure way. The cloud provider also provides guidance, transparency, guardrails, and innovative insurance options to help customers measure and mitigate their cloud risks.

Shared fate also involves the cloud provider and the customer interacting more closely and collaboratively to address cloud security challenges. The cloud provider listens to the customer’s feedback and needs, and provides solutions that meet their security requirements. The customer trusts the cloud provider’s expertise and follows their best practices and recommendations. The cloud provider and the customer share information and insights, and respond to security incidents together.

Shared fate is a better way to manage cloud risk because it creates a win-win situation for both parties. The cloud provider benefits from having more satisfied and loyal customers, as well as a more secure and resilient cloud platform. The customer benefits from having more secure and reliable workloads, as well as a more trusted

How Cloud Monitoring Can Boost Your DevOps Success

cloud monitoing, cybersecurity, observability

DevOps is a culture and practice that aims to deliver high-quality software products and services faster and more efficiently. DevOps involves the collaboration and integration of various roles and functions, such as development, testing, operations, security, and more. DevOps also relies on various tools and processes, such as code repositories, build pipelines, testing frameworks, deployment tools, and more.

However, DevOps also poses some challenges and risks, such as ensuring the reliability, availability, performance, security, and cost-efficiency of the software products and services. This is especially true when the software products and services are deployed on the cloud, which offers scalability, flexibility, and convenience, but also introduces complexity, variability, and uncertainty.

This is where cloud monitoring comes in. Cloud monitoring is the process of collecting and analyzing data and information from cloud resources, such as servers, containers, applications, services, etc. Cloud monitoring can help DevOps teams to achieve their goals and overcome their challenges by providing them with insights and feedback on various aspects of their cloud-based software products and services.

In this blog post, we will explore how cloud monitoring can boost your DevOps success in four ways:

• Cloud monitoring enables proactive problem detection and resolution: Cloud monitoring can help you to detect and resolve problems before they affect your end-users or your business outcomes. By using cloud monitoring tools, you can collect and analyze various metrics and logs from your cloud resources, such as CPU, memory, disk, network, latency, errors, etc. You can also set up alerts and notifications to inform you of any anomalies or issues that may indicate a potential problem. This way, you can quickly identify the root cause of the problem and take corrective actions to fix it.

• Cloud monitoring facilitates performance optimization and cost efficiency: Cloud monitoring can help you to optimize the performance and scalability of your cloud-based software products and services by providing you with insights into resource utilization, load balancing, auto-scaling, etc. You can use cloud monitoring tools to measure and benchmark the performance of your cloud resources against your expectations and requirements. You can also use cloud monitoring tools to adjust and optimize your resource allocation and configuration to meet the changing demands and conditions of your end-users and your environment. Additionally, cloud monitoring can help you to reduce the cost of your cloud operations by providing you with visibility into resource consumption, billing, and budgeting. You can use cloud monitoring tools to track and analyze your cloud spending and usage patterns. You can also use cloud monitoring tools to set up limits and alerts to prevent overspending or underutilization of your cloud resources.

• Cloud monitoring supports continuous delivery and integration: Cloud monitoring can help you to achieve continuous delivery and integration of your cloud-based software products and services by providing you with feedback and validation throughout the development and deployment lifecycle. You can integrate cloud monitoring tools with other DevOps tools and processes, such as code repositories, build pipelines, testing frameworks, deployment tools, etc. You can use cloud monitoring tools to monitor the quality and functionality of your code changes as they are integrated into the main branch. You can use cloud monitoring tools to measure and benchmark the performance of your cloud resources against your expectations and requirements. You can also use cloud monitoring tools to adjust and optimize your resource allocation and configuration to meet the changing demands and conditions of your end-users and your environment. Additionally, cloud monitoring can help you to reduce the cost of your cloud operations by providing you with visibility into resource consumption, billing, and budgeting. You can use cloud monitoring tools to track and analyze your cloud spending and usage patterns. You can also use cloud monitoring tools to set up limits and alerts to prevent overspending or underutilization of your cloud resources.

• Cloud monitoring supports continuous delivery and integration: Cloud monitoring can help you to achieve continuous delivery and integration of your cloud-based software products and services by providing you with feedback and validation throughout the development and deployment lifecycle. You can integrate cloud monitoring tools with other DevOps tools and processes, such as code repositories, build pipelines, testing frameworks, deployment tools, etc. You can use cloud monitoring tools to monitor the quality and functionality of your code changes as they are integrated into the main branch. You can also use cloud monitoring tools to monitor the status and health of your deployments as they are rolled out to different environments or regions. This way, you can ensure that your software products and services are always in a deployable state and meet the quality standards and expectations of your end-users and your stakeholders.

• Cloud monitoring fosters collaboration and communication: Cloud monitoring can help you to improve collaboration

Cloud Security Monitoring Trends

cloud monitoing, cybersecurity

Cloud security monitoring helps organizations detect and respond to threats, vulnerabilities, misconfigurations, compliance violations, and incidents in their cloud environments.

Cloud security monitoring is becoming more important and challenging as organizations adopt cloud services at an increasing rate and face new and evolving risks in the cloud. According to Gartner, 92% of organizations currently host their IT environment in the cloud, but with major advantages follow some critical security threats.

In this article, we will explore some of the key trends and developments that will shape the cloud security monitoring landscape in 2023 and beyond.

Trend 1: Cloud Security Posture Management (CSPM)

One of the main challenges of cloud security monitoring is the lack of visibility and control over the configuration and status of cloud resources and services. Misconfiguration, lack of visibility, identity, and unauthorized access are among the highest-ranked cloud threats, according to a survey by Oracle and KPMG.

Cloud Security Posture Management (CSPM) is a solution that helps organizations address this challenge by continuously assessing and improving their cloud security posture. CSPM tools automate the discovery and remediation of cloud misconfigurations, enforce security policies and best practices, provide compliance assurance, and generate reports and dashboards for visibility and accountability.

CSPM is expected to grow in demand and adoption this year, as organizations realize the benefits of proactive and preventive cloud security monitoring. According to Gartner, by 2024, 80% of cloud breaches will be due to customer misconfiguration, mismanaged credentials or insider theft, which CSPM tools can help prevent or mitigate.

Trend 2: Data Protection Before It Reaches the Cloud

Another challenge of cloud security monitoring is ensuring the protection of sensitive data that is stored or processed in the cloud. Data loss and leakage are among the top cloud security concerns in 2021, according to a report by Netwrix.

Data protection in the cloud involves encrypting data at rest and in transit, applying access controls and permissions, implementing data loss prevention (DLP) policies, and monitoring data activity and anomalies. However, these measures may not be enough to prevent data breaches or comply with data privacy regulations.

Therefore, some organizations are adopting a more proactive approach to data protection by encrypting or anonymizing data before it reaches the cloud. This way, they can reduce the risk of exposing sensitive data to unauthorized parties or compromising their data sovereignty.

One example of this approach is Bring Your Own Key (BYOK) encryption, which allows organizations to use their own encryption keys to encrypt data before sending it to the cloud. This gives them more control over their data security and access. However, BYOK encryption also requires careful management of the encryption keys and compatibility with the cloud service providers.

Trend 3: Digital Supply Chain Risk Management

The digital supply chain refers to the network of vendors, partners, suppliers, and customers that provide or consume digital products or services. The digital supply chain can introduce new risks for cloud security monitoring, as attackers can exploit vulnerabilities or compromise third-party components or services to gain access to target systems or data.

The SolarWinds breach in 2020 was a prominent example of a digital supply chain attack that affected thousands of organizations worldwide. The attackers inserted malicious code into a software update from SolarWinds, a network management software provider, which then infected its customers’ systems.

To prevent or mitigate such attacks, organizations need to adopt a holistic approach to digital supply chain risk management. This involves identifying and assessing the risks associated with their digital supply chain partners, implementing security standards and controls for third-party access and integration, monitoring their digital supply chain activity and performance, and responding to incidents or alerts promptly.

Trend 4: Vendor Consolidation

The cloud security monitoring market is fragmented and complex, with many vendors offering different products and services for various aspects and layers of cloud security. This can create challenges for organizations such as interoperability issues, redundant features, inconsistent policies or vendor lock-in. Therefore, some organizations are looking for more integrated and comprehensive solutions for cloud security monitoring that can reduce complexity, cut costs, and improve efficiency. This leads to a trend of vendor consolidation where vendors merge, acquire, or partner with other vendors
to offer more complete
and unified platforms for cloud security monitoring

Some examples of vendor consolidation in the cloud security monitoring space are:

Vendor consolidation can offer benefits for organizations such as:

  • Simplified procurement and management of cloud security monitoring tools
  • Enhanced visibility and correlation across multiple sources and types of data
  • Improved scalability and performance of cloud security monitoring solutions

However, vendor consolidation can also introduce some challenges such as:

  • Reduced negotiating power and flexibility with vendors
  • Potential single points of failure or compromise in case of vendor breaches or outages
  • Increased dependency on vendor support or updates

Summary

Cloud security monitoring is a vital function for organizations that use cloud services for their IT operations and business processes. Cloud security monitoring helps organizations detect and respond to threats, vulnerabilities, misconfigurations compliance violations, and incidents in their cloud environments.

However, cloud security monitoring is also evolving rapidly as organizations face new and emerging risks in the cloud. Some of the key trends that will shape the cloud security monitoring landscape in this year are:

  • Cloud Security Posture Management (CSPM)
  • Data Protection Before It Reaches the Cloud
  • Digital Supply Chain Risk Management
  • Vendor Consolidation

Organizations need to be aware of these trends and adapt their strategies, tools, processes and skills accordingly to ensure effective efficient and secure cloud security monitoring in this year and beyond.

Cloud Native Security: Cloud Native Application Protection Platforms

cloud monitoing, cybersecurity, monitoring, network observability, observability

Back in 2022, 77% of interviewed CIOs stated that their IT environment is constantly changing. We can only guess that this number, would the respondents be asked today, will be as high as 90%+. Detecting flaws and security vulnerabilities becomes more and more challenging in 2023 since the complexity of typical software deployment is exponentially increasing year to year. The relatively new trend of Cloud Native Application Protection Platforms (CNAPP) is now supported by the majority of cybersecurity companies, offering their CNAPP solutions for cloud and on-prem deployments.

CNAPP rapid growth is driven by cybersecurity threats, while misconfiguration is one of the most reported reasons for security breaches and data loss. While workloads and data move to the cloud, the required skill sets of IT and DevOps teams must also become much more specialized. The likelihood of an unintentional misconfiguration is increased because the majority of seasoned IT workers still have more expertise and got more training on-prem than in the cloud. In contrast, a young “cloud-native” DevOps professional has very little knowledge of “traditional” security like network segmentation or firewall configuration, which will typically result in configuration errors.

Some CNAPP are proud to be “Agentless” eliminating the need to install and manage agents that can cause various issues, from machine’ overload to agent vulnerabilities due to security flows and, guess what, due to the agent’s misconfiguration. Agentless monitoring has its benefits but it is not free of risks. Any monitored device should be “open” for such monitoring, typically coming from a remote server. If an adversary was able to fake a monitoring attempt, he can easily get access to all the monitored devices and compromise the entire network. So “agentless CNAPP” does not automatically mean a better solution than a competing security platform. Easier for maintenance by IT staff? Yes, it is. Is it more secure? Probably not.

Machine Learning for Network Security, Detection and Response

artificial intelligence, cloud monitoing, cybersecurity, deep observability

Cybersecurity is the defense mechanism used to prevent malicious attacks on computers and electronic devices. As technology becomes more advanced, it will require more complex skills to detect malicious activities and computer networks’ flaws. This is where machine learning can help.

Machine learning is a subset of artificial intelligence that uses algorithms and statistical analysis to make assumptions about a computer’s behavior. It can help organizations address new security challenges, such as scaling up security solutions, detecting unknown and advanced attacks, and identifying trends and anomalies. Machine learning can also help defenders more accurately detect and triage potential attacks, but it may bring new attack surfaces of its own.

Machine learning can be used to detect malware in encrypted traffic, find insider threat, predict “bad neighborhoods” online, and protect data in the cloud by uncovering suspicious user behavior. However, machine learning is not a silver bullet for cybersecurity. It depends on the quality and quantity of the data used to train the models, as well as the robustness and adaptability of the algorithms.

A common challenge faced by machine learning in cybersecurity is dealing with false positives, which are benign events that are mistakenly flagged as malicious. False positives can overwhelm analysts and reduce their trust in the system. To overcome this challenge, machine learning models need to be constantly updated and validated with new data and feedback.

Another challenge is detecting unknown or zero-day attacks, which are exploits that take advantage of vulnerabilities that have not been discovered or patched yet. Traditional security solutions based on signatures or rules may not be able to detect these attacks, as they rely on prior knowledge of the threat. Machine learning can help to discover new attack patterns or adversary behaviors by using techniques such as anomaly detection, clustering, or reinforcement learning.

Anomaly detection is the process of identifying events or observations that deviate from the normal or expected behavior of the system. For example, machine learning can detect unusual network traffic, login attempts, or file modifications that may indicate a breach.

Clustering is the process of grouping data points based on their similarity or proximity. For example, machine learning can cluster malicious domains or IP addresses based on their features or activities, and flag them as “bad neighborhoods” online.

Reinforcement learning is the process of learning by trial and error, aiming to maximize a cumulative reward. For example, machine learning can learn to optimize the defense strategy of a system by observing the outcomes of different actions and adjusting accordingly.

Machine learning can also leverage statistics, time, and correlation-based detections to enhance its performance. These indicators can help to reduce false positives, identify causal relationships, and provide context for the events. For example, machine learning can use statistical methods to calculate the probability of an event being malicious based on its frequency or distribution. It can also use temporal methods to analyze the sequence or duration of events and detect anomalies or patterns. Furthermore, it can use correlation methods to link events across different sources or domains and reveal hidden connections or dependencies.

Machine learning is a powerful tool for cybersecurity, but it also requires careful design, implementation, and evaluation. It is not a one-size-fits-all solution, but rather a complementary approach that can augment human intelligence and expertise. Machine learning can help to properly navigate the digital ocean of incoming security events, particularly where 90% of them are false positives. The need for real-time security stream processing is now bigger than ever.

Gartner: “it is the user, not the cloud provider” who causes data breaches

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Gartner’s recommendations on cloud computing strategy open the rightful discussion on the roles and responsibilities of different actors involved in cloud security. How many security and data breaches happen due to Cloud Service Providers (CSP) flaws, and how many of them are caused by CSP’s customers and human beings dealing with the cloud on a daily base? Gartner predicts that through 2025 99% of cloud security failures will be the customer’s fault. Such a prediction can only be based on the current numbers that obviously should demonstrate that the vast majority of breaches come due to CSP clients’ issues.

Among other reason, the first place is taken by data breaches coming from misconfiguration of the cloud environment and security flaws in software that were missed by DevOps and IT teams working in the cloud.

While the workloads and data keep moving to the cloud, DevOps and IT teams often lack the required skill sets to properly configure and maintain cloud-based software. The likelihood of an unintentional misconfiguration is increased because the majority of seasoned IT workers have significantly more expertise and training with on-premises security than they do with the cloud. While younger, less experienced workers may be more acclimated to publishing data to the cloud, they may not be as familiar with dealing with security, which might result in configuration errors.

Some of the team members have near heard of the Roles Based Access Control (RBAC) principle and will have real trouble working in the cloud like AWS being required to properly set up IAM users and IAM roles for each software component and service. These DevOps and IT engineers need to take intensive training to close the cloud security gap. Until it is done the enterprise will keep struggling from improper configuration, production failures and periodic security breaches.

Simple solutions like a firewall can add an additional degree of security for data and workloads, either for on-prem, hybrid, or pure cloud deployments. And yet, even simple things like that add another dimension of IT complexity and risk due to possible misconfiguration because of a human mistake or a vulnerable historical software package.

Full Stack IT Observability Will Drive Business Performance in 2023

cloud monitoing, cybersecurity, monitoring, network observability

Cisco predicts that 2023 will be shaped by a few exciting trends in technology, including network observability with business correlation. Cisco’s EVP & Chief Strategy Officer Liz Centoni is sure that

To survive and thrive, companies need to be able to tie data insights derived from normal IT operations directly to business outcomes or risk being overtaken by more innovative competitors

and we cannot agree more.

Proper intelligent monitoring of digital assets along with distributed tracing should be tightly connected to the business context of the enterprise. Thus, any organization can benefit from actionable business insights while improving online and digital user experience for customers, employees, and contractors. Additionally, fast IT response based on artificial intelligence data analysis of monitored and collected network and assets events can prevent or at least provide fast remediation for the most common security threat that exists in nearly any modern digital organization: misconfiguration. 79% of firms have already experienced a data breach in the past 2 years, while 67% of them pointed to security misconfiguration as the main reason.

Misconfiguration of most software products can be timely detected and fixed with data collection and machine learning of network events and configuration files analyzed by network observability and network monitoring tools. An enterprise should require its IT departments to reach full stack observability, and connect the results with the business context. It is particularly important since we know that 99% of cloud security failures are customers’ mistakes (source: Gartner). Business context should be widely adopted as a part of the results delivered by intelligent observability and cybersecurity solutions.

Cloud Monitoring Market Size Estimations

cloud monitoing, cybersecurity, monitoring, network observability, observability

According to a marketing study, the global IT infrastructure monitoring market is supposed to grow at 13.6% CAGR reaching USD $64.5 in 2031. Modern IT infrastructure becomes increasingly more complex and requires new skills from IT personnel, often blurring the borders between IT staff, DevOps, and development teams. With the continued move from on-prem deployments to the enterprise cloud, IT infrastructure goes to the cloud as well, and thus IT teams have to learn basic cloud-DevOps skills, such as scripting, cloud-based scaling, events creation, and monitoring. Furthermore, no company today offers a complete monitoring solution that can monitor any network device and software component.

Thus, IT teams have to build their monitoring solutions piece by piece, using various mostly not interconnected systems, developed by different, often competing vendors. For some organizations, it also comes to compliance, such as GDPR or ISO requirements, and to SLAs that obligate the IT department to timely detect, report, and fix any issue with their systems. In this challenging multi-system and multi-device environment, network observability becomes the key to enterprise success. IT organizations keep increasing their budgets seeking to reach the comprehensive cloud and on-prem monitoring for their systems and devices, and force the employees to run network and device monitoring software on their personal devices, such as mobile phones and laptops. This trend also increases the IT spend on cybersecurity solutions such as SDR and network security analysis with various SIEM tools.

Strategies to Combat Emerging Gaps in Cloud Security

cloud monitoing, cybersecurity, deep observability, network observability, startup

As cloud clients input 2023 with a hybrid presence in multiple clouds, they work on prioritizing techniques to fight rising gaps in cloud security.

Most big agencies are getting access to cloud offerings in numerous public clouds, whilst preserving organization structures and personal clouds of their company’s facts centers.

One of the ways of closing these gaps in security could be adopting deep observability. We have already reviewed a few Deep Observability providers such as Gigamon. While Gigamon probably can be considered a current market leader in this relatively new and small market with under $2B annual market size, they still should watch out for the newcomers who come with shiny new products and great technologies under the hood.

CtrlStack is one of these startups and they recently got a second round of funding from Lightspeed VC, led by Kearny Jackson and Webb Investment Network.

The delivery of features and applications by today’s digital-first companies and developers is accelerating. Teams from information technology operations and software development must collaborate closely to do this, forming a practice known as DevOps. When events occur, they may involve any number of digital environment systems, including operations, infrastructure, code, or any combination of modifications made to any of them.

The CtrlStack platform connects cause and effect to make troubleshooting easier and incident root cause analysis faster by tracking relationships between components in a customer’s systems. Developers and engineers can solve problems quickly by giving DevOps teams the tools they need.

By forming an understanding graph of all of the infrastructure, interconnected offerings, and impact, CtrlStack can supply the full picture while capturing the devices’ modifications and relationships throughout the whole device stack. Using CtrlStack product DevOps groups can view dependencies, measure the impact of modifications and examine occasions in actual time.

Key capabilities of the platform encompass an occasion timeline that permits groups to browse and clear out out extrade occasions, without having to sift via log documents or survey users, and a visual representation that offers insights into operational data. Both of those capabilities additionally force dashboards for builders and DevOps groups.

Developers can also access their dashboards that give visibility for any modifications to code commits, configuration documents, or function flags, – all in one click. DevOps groups get a dashboard for root reason evaluation that permits them to seize all of the context for the time being they came about with a searchable timeline of dependencies displaying the whole impacted topology and impacted metrics.