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What is Agile Analytics?

Agile Analytics is our amazing platform for optimizing software operations. The platform allows teams to gain insights into their entire pipeline and integrates against all the tools used rather than being limited to Jira or Git. Agile Analytics integrates various systems like your project management system (Jira, Azure DevOps), monitoring systems (AWS CloudWatch, GCP Cloud Monitor, Azure Monitor),  collaborative communication systems (Slack, Teams or Discord), and continuous delivery (like Github, Gitlab or Bit Bucket). 

Agile Analytics is our amazing platform for optimizing software operations. The platform allows teams to gain insights into their entire pipeline and integrates against all the tools used rather than being limited to Jira or Git. Agile Analytics integrates various systems like your project management system (Jira, Azure DevOps), monitoring systems (AWS CloudWatch, GCP Cloud Monitor, Azure Monitor),  collaborative communication systems (Slack, Teams or Discord), and continuous delivery (like Github, Gitlab or Bit Bucket). Using this platform, teams can make more informed decisions and become data-driven!

How to measure productivity metrics of software teams

Understanding team performance is crucial for professionals in the tech industry, regardless of their role. It can be challenging to get a clear view of how teams are performing, but with the right tools and strategies, professionals can take their team's performance to the next level and achieve business goals more effectively. Practical tips include increasing team autonomy, balancing maintenance and feature work, and getting a grip on software development stock.

Assessing software development progress and its impact on production can be difficult, but there are tools and metrics available to gain a better understanding of team performance. Manually reviewing backlog items can provide insight, but automation is necessary for regular analysis. Objective metrics like Error Budgets can signal when to shift focus. The right metrics need to be identified to measure productivity accurately, such as DevOps DORA Metrics. Team culture is also important to consider, with tools like Kudos to gauge overall morale. Agile Analytics provides features to optimize workflows, measure team productivity using DORA metrics, and ensure a safe, fun, and engaging work environment.

['Error Budgets'](https://www.agileanalytics.cloud/features#errorbudgets) are a way to measure and manage the allowable amount of errors or downtime in a system or service. It involves setting a threshold for acceptable errors, and the remaining budget is used for making improvements or implementing preventative measures. This approach helps teams prioritize their efforts and resources to minimize the impact of errors and keep the system or service running smoothly.

Using Error Budgets, teams can automatically monitor their performance and receive alerts when their service level drops too low. This feature increases team autonomy and provides valuable insights into the quality of their service delivery.

- Monitors if your service level is inside or outside of 'budget'
- Improves the autonomy of your agile team
- Delivers actionable data about how you’re managing production

[Sprint Insights](https://www.agileanalytics.cloud/features#sprintinsights) is a feature that uses deep learning technology to determine whether a ticket represents **maintenance** or **feature work** and how much time is spent on each. This feature provides users with greater insight into their team's sprints, allowing them to make more data-driven decisions and focus on the areas that matter most. By analyzing millions of tickets from public sources, Sprint Insights provides accurate and comprehensive information, making it a valuable tool for teams looking to improve their productivity and efficiency.

- Creates insights in feature development balance
- Uses AI and machine learning to analyze your tickets
- Automatically registers the time spent on feature & non-feature work

[The Stocks](https://www.agileanalytics.cloud/features#stock) feature helps users manage their software development backlog, also known as their software stock. The Stocks feature in software development helps manage the backlog by tracking deployment cadence and identifying waste. It provides insights into the amount of work waiting to be released and helps identify bottlenecks and inefficiencies. This tool is helpful for improving the software delivery process, optimizing resources, and reducing costs associated with a high backlog. It shows unexecuted development changes, the productivity of the team, and relevant data about software stock and waste.

[The DORA metrics](https://www.agileanalytics.cloud/manage-devops-using-dora-metrics) are a set of performance metrics developed by Google's DevOps Research and Assessment team to help software development teams measure and improve their performance. These metrics are based on six years of research and are predictive of software delivery operational performance. The DORA metrics provide insights into successful deployments, end-to-end monitoring of feature realization, lead time for delivering value, service level, change failure rate, and operational productivity metrics. Teams can track these metrics continuously and automatically using the Agile Analytics platform. The DORA metrics feature is a valuable tool for any software development team looking to improve their performance and deliver better software faster. It provides clear and fair performance data, streamlines development processes, and creates happier developers while increasing engagement and motivation.

The Lost API Key feature in Agile Analytics is designed to help users scan their Git repositories for any lost API or private keys. If a lost key is found, users can quickly identify what happened, block the lost key, and resolve the incident, ensuring the safety and security of their systems.

This feature is particularly valuable for teams working on large software development projects where many keys may be in use, making it difficult to keep track of them all. By using Agile Analytics, users can quickly scan their repositories and identify any lost keys, preventing potential security breaches and ensuring the smooth operation of their systems.

- Get a clear insight into your teams’ software waste
- Figure out where software stock is created
- Automatically scan your Git repositories on ‘lost’ keys
- Easily mark the key and solve the incident

The Lost API Key feature is an important tool for teams looking to ensure the safety and security of their systems, particularly in high-risk environments where sensitive data may be at risk. With Agile Analytics, users can quickly identify and resolve incidents related to lost API or private keys, making it easier to maintain the integrity of their systems and safeguard their data.

The hour registration feature in the Agile Analytics platform allows users to quickly and easily register the number of hours worked. The platform also includes an inferred hours feature that suggests the number of hours worked based on the user's input. This all-in-one platform feature can help users keep track of their work hours accurately and efficiently.

The feature allows users to reward their team members with Kudos and celebrate their personal and team achievements. It also provides leaderboards to keep track of scores and encourage friendly competition. Overall, the feature promotes a fun and positive team dynamic and encourages collaboration and recognition among team members.

- Celebrate team achievements together.
- Reward each other with Kudos
- Have a little fun and recognize each other! (:balloon: , :star:, :+1:)

Are you tired of guesswork and unproductive software development cycles? Look no further than Agile Analytics! By integrating with all existing support tools, our platform provides critical insights into the health of your software operations and where to improve. With features like Error Budget, teams will know exactly when to push forward on feature development or break a sprint. Our Deep Learning-powered dashboards empower software teams with the right metrics to become high-performing, all while reducing defects in production and cutting feature delivery time. 

**Say goodbye to unproductive cycles and hello to Agile Analytics!**

Visit our [website](https://www.agileanalytics.cloud/) or contact us at <hello@agileanalytics.cloud> to learn more.

ZEN Software releases Agile Analytics Cloud

After 30 months of coding, designing, debating and bugfixing we’re proud and happy to announce we are releasing Agile Analytics to the general public!
 

Agile Analytics is now GA
Why should your organisation use Agile Analytics?

**For Development Managers**
- Match or challenge gut feeling with real data
- Reward collaborative behaviour
- Manage Developer Experience (DX)

**For Teams & Agile Coaches**
- Improve autonomy: Make decisions for yourselves
- OKR /  SLA : promise vs reality
- Actionable & real-time performance data:  ‘how are we really doing?’

After 30 months of coding, designing, debating and bugfixing we’re proud and happy to announce we are releasing Agile Analytics to the general public!

Why should your organisation use Agile Analytics?

**For Development Managers**
- Match or challenge gut feeling with real data
- Reward collaborative behaviour
- Manage Developer Experience (DX)




**For Teams & Agile Coaches**
- Improve autonomy: Make decisions for yourselves
- OKR /  SLA : promise vs reality
- Actionable & real-time performance data:  ‘how are we really doing?’



Agile Analytics integrates with a wide variety of Software Development systems that enables real insight into your software operation 

Measure the Team Spirit using Leaderboards, reward team behaviour

Measure the balance between feature work and non-feature work

How are your team’s services performing? are they performing like the teams promised? 

match SLA/SLO to real-time monitoring systems and see if the team is focusing in ‘the right thing’

Detect previously undetected leaks in your code by scanning the repositories for lost keys and see how much work is 'in process’. How is the software 'stock' situation? are the teams regularly releasing new changes or are queues forming inside your software operation?

Agile Analytics now supports Sprint Insights

Agile Analytics allows you to integrate Jira project management to determine what of the completed (or created) tasks qualify as

- feature
- non-feature


ZEN Software created a machine learning classification algorithm to teach Agile Analytics what is a ‘feature’ and what not.
To help improve the accuracy you as user of Agile Analytics can train the model for your organisation.

This great new innovation allows Development Manager and Agile Coaches everywhere to see how the pace of feature dev is! 



Agile Analytics allows you to integrate Jira project management to determine what of the completed (or created) tasks qualify as

- feature
- non-feature


ZEN Software created a machine learning classification algorithm to teach Agile Analytics what is a ‘feature’ and what not

To help improve the accuracy you as user of Agile Analytics can train the model for your organisation.

This great new innovation allows Development Manager and Agile Coaches everywhere to see how the pace of feature dev is! 

Also it saves a lot of time running down ticket lists and pondering what tasks are ‘feature’ and what not.


From Riches to Rags: How Leaked Private Keys Led to the Disappearance of Code Spaces

In the world of software development, security breaches are an ever-looming threat. In June 2014, one company fell victim to a vicious cyberattack that ultimately led to its demise. This cautionary tale is a stark reminder of the importance of safeguarding sensitive information and highlights the need for Agile Analytics to mitigate such risks. 

In the world of software development, security breaches are an ever-looming threat. In June 2014, one company fell victim to a vicious cyberattack that ultimately led to its demise. This cautionary tale is a stark reminder of the importance of safeguarding sensitive information and highlights the need for Agile Analytics to mitigate such risks. Let's dive into the chilling account of Code Spaces and the catastrophic consequences they faced.

It all began when Code Spaces, a renowned code-hosting and collaboration platform, was under siege. A Distributed Denial of Service (DDoS) attack battered their defences. The perpetrators saw an opportunity to exploit a vulnerability and launched a full-scale assault on Code Spaces' infrastructure. The attackers had one motive: chaos. But little did they know how devastating their actions would be.

In an attempt to regain control and ward off the attack, Code Spaces' cloud team faced a harsh reality—their AWS management console had been compromised. The attackers infiltrated the heart of their system, gaining unauthorized access. The consequences were dire; the attackers started deleting critical data. A malevolent force that would soon bring Code Spaces to its knees.

As the attackers tightened their grip on Code Spaces, they unleashed a torrent of destruction. Valuable customer data and countless customer projects vanished into thin air. The devastation was absolute. The attackers seemed hell-bent on erasing any trace of Code Spaces' existence, leaving behind a bleak landscape of scorched earth.

In the face of such a catastrophic breach, Code Spaces' resilient team fought back. They sought to regain control of the data, salvaging what they could from backups. But the extent of the damage proved insurmountable as all the backups were corrupted or wiped by the attackers. Their failure to implement adequate backups and disaster recovery mechanisms left them helpless.

With their reputation tarnished and customer trust shattered, Code Spaces confronted a difficult decision. Their once-vibrant platform, a thriving collaboration hub, could no longer provide the reliability and security their customers deserved. In a heart-wrenching announcement, Code Spaces bid farewell to their users, acknowledging the impossibility of rebuilding what was lost.

Organisations must adopt proactive measures to protect their software and sensitive information in the face of lurking threats and potential devastation. [Agile Analytics](https://www.agileanalytics.cloud) is a formidable SaaS solution to mitigate the risks of leaked private keys, real-time DORA metrics and easy management of Error Budgets. By employing cutting-edge Cloud SaaS technology, you can scan your software, identify vulnerabilities, and take swift action to safeguard your organization from potential sabotage. Don't wait for disaster to strike—embrace the power of Agile Analytics today.

Code Spaces serves as a chilling reminder of the dangers related to security. Years of hard work and innovation were obliterated in a single stroke of malevolence. But from the ashes of this cautionary tale rises an opportunity for change. By embracing scanning and Agile Analytics, organisations can fortify their defence and ensure the security of their infrastructure. Don't let your organisation become the next victim—take control and protect what matters most.

No more Manual Hassles! Automate Your Non-Functional Measurement for Maximum Efficiency!

Software quality goes beyond functionality. Non-functional aspects like **performance**, **reliability**, and **security** are crucial. Our Agile Analytics SaaS platform offers a comprehensive solution to manage and measure these dimensions effectively. By leveraging DORA metrics and SRE Error Budgets, teams can optimise deployment, reliability, and security, while also monitoring software stock and detecting leaked private keys.

Software quality goes beyond functionality. Non-functional aspects like **performance**, **reliability**, and **security** are crucial. Our Agile Analytics SaaS platform offers a comprehensive solution to manage and measure these dimensions effectively. By leveraging DORA metrics and SRE Error Budgets, teams can optimise deployment, reliability, and security, while also monitoring software stock and detecting leaked private keys.

**1. [DORA Metrics](https://www.agileanalytics.cloud/manage-non-functional-quality-management-metrics-performance-reliability-security#dorametrics)**: Measure Deployment Frequency and MTTR Agile Analytics SaaS integrates  [DORA Metrics](https://www.agileanalytics.cloud/manage-non-functional-quality-management-metrics-performance-reliability-security#dorametrics), providing insights into deployment frequency and Mean Time between failure (MTTR). These metrics optimise software agility, adaptability, and recovery time, enabling data-driven decisions for continuous improvement.

**2. [SRE Error Budgets](https://www.agileanalytics.cloud/manage-non-functional-quality-management-metrics-performance-reliability-security#errorbudgets)**: Enhancing Reliability The platform introduces [SRE Error Budgets](https://www.agileanalytics.cloud/manage-non-functional-quality-management-metrics-performance-reliability-security#errorbudgets), defining acceptable error rates and quantifying software reliability. Monitoring error budgets allows proactive adjustments in planning and resource allocation to maintain reliability and enhance end-user satisfaction.

**3. Quantify [Software "Stock"](https://www.agileanalytics.cloud/manage-non-functional-quality-management-metrics-performance-reliability-security#softwarestock) and Detect [Leaked Private Keys](https://www.agileanalytics.cloud/manage-non-functional-quality-management-metrics-performance-reliability-security#leakedprivatekeys)**. Agile Analytics SaaS introduces innovative metrics to measure [software "stock"](https://www.agileanalytics.cloud/manage-non-functional-quality-management-metrics-performance-reliability-security#softwarestock) and detect[ leaked private keys](https://www.agileanalytics.cloud/manage-non-functional-quality-management-metrics-performance-reliability-security#leakedprivatekeys). Quantifying [software "stock"](https://www.agileanalytics.cloud/manage-non-functional-quality-management-metrics-performance-reliability-security#softwarestock) improves workflow efficiency, while detecting [leaked private keys](https://www.agileanalytics.cloud/manage-non-functional-quality-management-metrics-performance-reliability-security#leakedprivatekeys) safeguards sensitive data and prevents security breaches.

To excel in the digital landscape, software quality must prioritise non-functional aspects. The Agile Analytics SaaS platform **empowers** teams to optimise deployment, reliability, security, and workflow efficiency. By leveraging **[DORA Metrics](https://www.agileanalytics.cloud/manage-non-functional-quality-management-metrics-performance-reliability-security#dorametrics)** and SRE **[Error Budgets](https://www.agileanalytics.cloud/manage-non-functional-quality-management-metrics-performance-reliability-security#errorbudgets)**, organisations can make **data-driven decisions** for **continuous improvement**. Additionally, monitoring [software "stock"](https://www.agileanalytics.cloud/manage-non-functional-quality-management-metrics-performance-reliability-security#softwarestock) and detecting [leaked private keys](https://www.agileanalytics.cloud/manage-non-functional-quality-management-metrics-performance-reliability-security#leakedprivatekeys) ensures **enhanced productivity** and **security**. With Agile Analytics SaaS, automate your non-functional quality management and maximise your team’s ability to deliver!

I’m ready to supercharge non-functional quality management

Traditional Analytics or Agile Analytics: which one fits you best?

 In this article, we explore the key differences between Agile Analytics and Traditional Analytics to help organisations make informed decisions about their analytical strategies.

All organisations do analytics to extract insights from their data. Some organisations even make most of their decisions based on this data. Are there any distinct ways in which we can do analytics? We’ve found two prominent approaches: Agile Analytics and Traditional Analytics. Each has its own set of principles, practices, and advantages. In this article, we explore the key differences between Agile Analytics and Traditional Analytics to help organisations make informed decisions about their analytical strategies.

As the name suggests, this form of analytics has been around since Big Gates was modelling on his desk back when Microsoft was still a cool startup.

**Sequential Process:**

Traditional Analytics typically follows a sequential, waterfall-like process. It involves distinct phases such as data collection, cleansing, transformation, analysis, and reporting. Each phase is completed before moving on to the next, often resulting in lengthy project timelines.

**Rigorous Planning:**

In the traditional approach, extensive planning is done upfront to define requirements and scope. Changes to the project scope are often challenging to accommodate once the project is underway.

**Fixed Scope and Deliverables:**

Projects are planned with fixed scope and deliverables, making it challenging to adapt to evolving business needs or to incorporate new data sources during the project.

**Comprehensive Documentation:**

 Documentation is a key aspect of traditional analytics. Detailed documentation is created at each stage to provide a comprehensive understanding of the entire process.

**Long Development Cycles:**

The emphasis on thorough planning and documentation often leads to longer development cycles, and insights are delivered at the end of the project.

Since the early 2010s everything needed to become ‘agile’, because as we learnt everything is agile is better? well, it depends but for analytics, approaching things in a more ‘agile’ fashion actually makes sense

**Iterative and Incremental:**

 Agile Analytics, inspired by the principles of Agile software development, adopts an iterative and incremental approach. It divides the project into smaller, manageable iterations or sprints, each delivering a potentially shippable product increment.

**Adaptive Planning:**

 Agile Analytics embraces adaptive planning, allowing teams to respond to changing requirements and priorities. Planning is continuous and flexible, enabling adjustments based on ongoing feedback.

**Embraces Change:**

 One of the core principles of Agile is its adaptability to change. Agile Analytics acknowledges that requirements evolve throughout the project, and it accommodates changes to ensure that the end product aligns with business needs.

**Collaboration and Communication:**

 Agile places a strong emphasis on collaboration and communication within cross-functional teams. Regular meetings, such as daily stand-ups, facilitate constant communication and coordination among team members.

**Early and Continuous Delivery:**

 Agile Analytics aims for early and continuous delivery of insights. This allows stakeholders to gain value incrementally throughout the project, rather than waiting for a comprehensive solution at the project's end.

Agile Software Development and Agile Analytics go hand in hand, sharing principles of flexibility and collaboration. Aligning analytics with an Agile mindset is crucial for the following reasons:

1. **Rapid Adaptation:** Agile development involves frequent requirement changes. Agile Analytics is flexible and adapts quickly to evolving project needs.
2. **Frequent Releases:** Agile development operates on short cycles. Agile Analytics ensures rapid insights to support the quick-release cadence of Agile teams.
3. **Collaborative Decision-Making:** Agile promotes team collaboration. Agile Analytics involves stakeholders, ensuring insights align with business goals.
4. **User-Centric Focus:** Agile emphasizes delivering value to users. Agile Analytics provides rapid feedback on user behaviour, enhancing user-centric solutions.

In summary, aligning analytics with an Agile mindset promotes collaboration, flexibility, and continuous improvement, ensuring timely and relevant insights for Agile development teams. This integrated approach supports data-driven decision-making and contributes to overall project success.

Experience ZEN Software’s Agile Analytics

The next step is to employ an Analytics platform based on the same tenets for your Software Development. With Agile Analytics, you measure critical metrics like feature/non-feature balance, deployment frequency, and SRE Error budgets and monitor DORA metrics and Error Budgets.

Measuring Error Budgets in Agile Analytics

Gain unparalleled visibility into your sprint performance. Don't miss this chance to break free from traditional constraints and propel your organization to new heights.

We can help you out with a DevOps Assessment, Continuous Delivery conversion, a Lean Software Development Transformation or an SRE implementation. Start your Agile Analytics journey today!

Agile Analytics now support AWS Cloud Watch



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- Choose AWS Cloud Watch
- Configure the details and press ‘test’
- Then under ‘SRE & Error Budget’ you can add a feature to a service and configure the cloud watch metrics copied from the Cloud Watch Console



Rectangular Azure font software screenshot highlighting technological features of software.

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"Rectangle/circle w/text to setup AWS CloudWatch:

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Configure the details and press ‘test’

Then under ‘SRE & Error Budget’ you can add a feature to a service and configure the cloud watch metrics copied from the Cloud Watch Console


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Press ‘create’

here is an example of the code you need to copy from Cloud watch

Once configured you’ll see the error budgets managed for your teams



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For more information, please reach out to [ZEN Software’s Support](https://www.agileanalytics.cloud/contact?slug=contact).