In today’s issue, we will discuss a few trends and industry reports from last year, which will follow us this year, too. Namely:
2025 Gartner Top 10 Strategic Technology Trends
DORA Accelerate State of DevOps 2024.
Octoverse: Python has become the most popular language on GitHub
State of Cloud Security 2024 by DataDog
State of JavaScript 2024.
So, let’s dive in.
2025 Gartner Top 10 Strategic Technology Trends
Gartner recently shared a new set of strategic technology trends that will shape our future and drive innovation.
Here are the major trends:
1. ⚙️ Agentic AI
Agentic AI represents the next evolution in autonomy, enabling systems to make decisions independently to optimize processes. This goes beyond chatbots, allowing organizations to use AI for complex tasks like autonomous decision-making in customer service, operations, and data analysis.
➡️ Future Impact: Gartner predicts that 15% of daily work decisions will be autonomous by 2028, streamlining workflows and boosting productivity.
2. 📜 AI Governance Platforms
As AI becomes integral to sensitive operations, AI governance platforms ensure transparency, fairness, and accountability. These platforms manage AI ethics, compliance, and model accuracy, which is critical for regulated industries.
➡️ Future Impact: By 2028, organizations with strong AI governance frameworks will see a 30% increase in customer trust and 25% better regulatory compliance scores.
3. 🕵️♂️ Disinformation Security
As digital misinformation grows, enterprises need tools to detect deepfakes, prevent impersonation, and verify content authenticity. This trend addresses the rising risk of data manipulation in social media, marketing, and internal communications.
➡️ Future Impact: By 2028, over 50% of enterprises will deploy systems to address disinformation threats.
4. 🔒 Post-Quantum Cryptography (PQC)
Quantum computing poses a significant threat to current encryption standards. Post-quantum cryptography aims to secure data against quantum-based decryption, which is essential for long-term protection.
➡️ Future Impact: Transitioning to PQC will become essential by 2029, as quantum advancements render traditional encryption obsolete.
5. 🌐 Ambient Invisible Intelligence
This trend leverages low-cost sensors and cloud integration to create seamless, automated environments. From smart cities to healthcare and retail, ambient intelligence enhances efficiency without requiring active user interaction.
➡️ Why it matters: Smart homes and cities will have systems that will adjust automatically to optimize energy, traffic, and healthcare operations without user input.
6. 🔋 Energy-Efficient Computing
As sustainability becomes central, energy-efficient computing methods will reduce the environmental impact of data centers, AI, and IT infrastructure. Technologies like GPUs and neuromorphic chips are leading this transformation.
➡️ Future Impact: New energy-efficient technologies, like GPUs and neuromorphic chips, aim to curb IT’s carbon footprint, which is crucial for organizations committed to sustainability.
7. ☁️ Hybrid Computing
It blends CPU, GPU, quantum, and neuromorphic systems to handle complex tasks. This setup allows organizations to optimize costs, performance, and security by leveraging cloud and on-premises resources.
➡️ Future Impact: By 2030, hybrid systems will dominate industries like finance and healthcare, enabling real-time, secure computation for critical workloads.
8. 🌍 Spatial Computing
Advancements in AR and VR are pushing spatial computing, allowing users to interact with digital content in a real-world context. Use cases are expanding into remote work, immersive training, and e-commerce experiences.
➡️ Future Impact: The spatial computing market is expected to grow from $110 billion in 2023 to $1.7 trillion by 2033, driven by consumer demand and business adoption.
9. 🤖 Polyfunctional Robots
Robots, designed to handle many tasks in dynamic environments, are gaining traction. Industries like manufacturing and healthcare are deploying robots to assist with logistics, maintenance, and service tasks.
➡️ Future Impact: By 2030, 80% of people will interact with smart robots daily, compared to just 10% today.
10. 🧠 Neurological Enhancement
Brain-machine interfaces enable it, promising cognitive improvement and personalized experiences. This technology could reshape healthcare, workforce productivity, and even marketing.
➡️ Future Impact: Early applications of brain-computer interfaces will focus on enhancing focus, treating neurological disorders, and enabling rapid skill acquisition.
👉 Check more from the report.
These trends represent the cutting edge of technology set to transform industries and drive innovation. Organizations that adopt these technologies strategically will be better positioned to navigate the future with agility and resilience.
Which of these trends excites you the most? How do you see them impacting your work or industry? Let me know!
DORA Accelerate State of DevOps 2024.
For the past decade, the DevOps Research and Assessment (DORA) team, now part of Google Cloud, has been the industry's most reliable source for monitoring software development performance. DORA's report, with data from over 39,000 professionals, has become the gold standard for determining what works in software development.
The DORA Report focuses on four key metrics, categorized into throughput and stability metrics, that indicate the performance of software delivery teams.
1. Throughput
⏱️ Change Lead Time: Time taken from committing code to deploying it
🔄 Deployment Frequency: How often code is deployed
2. Stability
📉 Change Failure Rate: Percentage of changes that fail and need remediation
⏳ Failed Deployment Recovery Time: Time to restore service after a failed deployment
Elite performers can deploy multiple times daily, recover from failures in less than an hour, and have change failure rates as low as 5%.
Here are the key insights from the report:
1. 🚀 The Impact of AI Adoption is Higher Productivity (almost)
The 2024 report focuses on how AI adoption affects development teams. AI is currently a reality at various stages of software development, with 81% of organizations using it. AI improves productivity, workflows, and job happiness for many developers. It also improves code quality, internal documentation, and review processes.
Regarding adoption, 75% of respondents said they use AI for at least one of their everyday tasks. AI was most commonly employed for code generation and information summarization here, which is consistent with feedback from across the Salesforce ecosystem.
While AI is widely used in everyday employment, trust difficulties persist. 40% of respondents stated they had little faith in AI-generated programming.
2. 📈 Platform Engineering is on the rise
Another trend explored in the report is the growth of platform engineering. The idea is to create internal platforms that allow developers to focus solely on coding while the platform handles repetitive tasks, such as infrastructure provisioning and automated testing. This approach significantly boosts productivity, with some teams seeing a 10% performance increase using internal platforms.
Implementing internal development platforms increased team and individual developer productivity by 10% and 8%, respectively. However, stability (14%) and change throughput (8%) were sacrificed.

3. 👩💻 Developer experience is critical to success
Teams prioritize user demands to increase productivity and product quality. Furthermore, a user-centric strategy lowers developer burnout and guarantees that solutions satisfy user needs, raising job satisfaction.
Unfortunately, in technical circles, burnout is an issue that is all too familiar. The study also discovered that burnout is higher in firms with erratic organizational priorities, where priorities change often.
The report concludes that AI is powerful but cannot perform miracles. Elite performance is more about continuous improvement and experimentation while remaining user-focused.
👉 Check the full report.
🐙 Octoverse: Python has become the most popular language on GitHub
The Octoverse 2024 report was issued on October 29 and covers GitHub data from October 1, 2023, to September 30, 2024, on open-source projects.
Here are the most important trends:
1. Python is the king
For the first time, Python has surpassed JavaScript to become the most widely used and fastest-growing programming language on GitHub. This trend is primarily due to Python's versatility and its role in data science, machine learning, artificial intelligence, and automation.
While Python and JavaScript hold the top spots, with JavaScript declining and TypeScript rising, there's notable growth in systems programming languages like Rust and Go (even though Rust is still not in the top 10). This trend indicates a rising interest in performance, safety, and concurrency in software development.
Languages such as Java and C# are widely used and ranked in the top 5.
Along with these languages, we see the fast rise of HCL, Kotlin, and Dart.
2. Explosion of Jupyter Notebooks usage
The report indicates a 92% increase in the use of Jupyter Notebooks. This trend shows the growing interest in data analysis, scientific computing, and machine learning. Jupyter Notebooks give an interactive environment that combines code execution with rich text elements, making them a good choice for data scientists and researchers.
3. Global rise in Generative AI projects
There's been a 98% increase in Generative AI projects and a 59% in contributions to these projects. Developers worldwide are integrating AI models into applications, exploring new possibilities, and working with AI projects. While the United States leads in contributions, significant activity comes from countries like India, Germany, Japan, and Singapore. Other communities saw some of the highest percentage growth in contributors to public generative AI projects, like the Netherlands (291%), Ethiopia (242%), Costa Rica (171%), Serbia (175%), and Vietnam (143%).
The top public generative AI projects are:
AUTOMATIC1111/stable-diffusion-webui (image generation)
Significant-Gravitas/AutoGPT (AI Agent development)
ollama/ollama (the fastest-growing open-source AI project in 2024)
4. Strong growth of the global developer community
The developer community on GitHub is expanding very fast, especially in Africa, Latin America, and Asia. India is projected to have the world's largest developer population on GitHub by 2028. This growth is partly due to students and educators, with over 7 million participants in the GitHub Education program. Tools like GitHub Copilot have seen 100% year-over-year growth among students, teachers, and open-source maintainers, which can be related to AI trends.
👉 Check the full report.
State of Cloud Security 2024 by DataDog
The DataDog report shows the landscape of cloud-native threats and the importance of understanding attacker behaviors and risk patterns. Analyzing data from thousands of organizations using AWS, Azure, or Google Cloud, the report reveals improvements and ongoing challenges in cloud security practices.
Here are the key findings:
1. Long-lived credentials remain a significant risk
Long-lived cloud credentials, such as access keys that never expire, continue to pose significant security threats due to their susceptibility to leakage through source code, container images, and application artifacts.46% of organizations still use IAM users with long-lived credentials; 25% use them exclusively in AWS.
To avoid long-lived credentials, use temporary, time-bound credentials. To minimize risks, implement centralized identity management solutions, such as AWS IAM Identity CID, and leverage roles for workloads.
2. Increased adoption of Public Access Blocks in Cloud Storage
Guardrails like public access blocks effectively reduce the number of publicly exposed storage buckets, a common source of data breaches. Enable public access blocks at the account level and protect configurations with service control policies.
3. Adoption of IMDSv2 in AWS EC2 Instances is growing
IMDSv2 is critical for preventing credential theft in EC2 instances, yet its enforcement is not universal. Enforce IMDSv2 across all EC2 instances, utilize secure-by-default mechanisms, and monitor credential usage to prevent unauthorized access.
4. Managed Kubernetes Clusters need enhanced security configurations
Default settings in managed Kubernetes services often lack essential security features, increasing vulnerability. To prevent cluster compromise, secure clusters by restricting API server access, enabling audit logs, and assigning minimal cloud permissions to worker nodes.
5. Insecure IAM Roles for third-party integrations pose risks
Third-party integrations can introduce supply chain vulnerabilities if not properly managed. Audit third-party integrations regularly, remove unused roles, grant minimal permissions, and enforce the use of External IDs to mitigate risks.
6. Most Cloud incidents stem from compromised credentials
Attackers frequently exploit compromised identities to gain initial access, noting the need for more secure authentication measures. Implement robust authentication methods like FIDO keys, limit long-lived credentials, and monitor for unusual API activities to prevent unauthorized access.
7. Excessive privileges and improper workload placement increase risks
Overprivileged workloads and inappropriate deployment practices expand the attack surface. To enhance security, assign workloads with minimal necessary permissions, avoid deploying in management accounts, and turn off default service account grants.
👉 Check the full report.
State of JavaScript 2024.
A few days ago, the results from the 2024 State of Javascript Survey, which examined new trends and technologies in web development, were published—the poll, which was funded by Google and other partners and received 14,015 replies.
The highlights of the report are:
1. 🚀 Most Adopted JavaScript Syntax Feature
The nullish coalescing operator (??
) took the top spot as the most widely adopted JavaScript syntax feature, reflecting its utility in handling null
or undefined
values efficiently.
2. 🌟 Front-End Frameworks
React continues to dominate the front-end framework space, with 82% adoption among respondents. It is followed by:
Vue.js (51%)
Angular (50%)
Svelte (26%)—which is steadily gaining popularity.
3. ⚡ Most Adopted Build Tool
Vite, a blazing-fast build tool and local development server for modern web apps, emerged as the most adopted technology, with 69% of developers using it. Its popularity reflects the growing demand for faster development workflows.
4. 🏆 Winner in Meta Frameworks
Next.js leads the meta-framework category, offering server-side rendering and static site generation for React-based web apps. Other frameworks, such as Remix, Astro, and SvelteKit, are gaining traction but remain below 20% adoption.
5. 🧰 Mono Repo Tools
Mono repo tools remain fragmented, with multiple solutions evenly utilized. However, pnpm stands out for its steady retention rate, showing its staying power in the ecosystem.
6. 🖥️ Back-End Frameworks
Express remains the most used back-end framework for JavaScript developers, with 68% adoption. Its reliability and extensive ecosystem continue to appeal to developers. Meanwhile, Nest.js has grown to 29% adoption, showing momentum as a modern back-end alternative.
7. 🔧 JavaScript Runtimes
Node.js is the clear leader in runtimes, chosen by 91% of respondents. However, newer runtimes are starting to make waves, as Bun received 16% mentions, making it the most discussed write-in option.
8. 🐍 Popular Companion Languages
When pairing JavaScript with other languages, developers most often use:
Python (39%)
PHP (29%)
Java (23%)
9. 📈 The Rise of TypeScript
TypeScript continues its upward trajectory:
67% of developers report using TypeScript more than JavaScript.
The largest segment of respondents now consists of developers who exclusively write TypeScript.
The 2024 report highlights how JavaScript and its ecosystem are evolving. While React, Node.js, and Express maintain their dominance, emerging tools like Vite, Svelte, and Bun are making significant strides. TypeScript’s rise also signals a shift towards more substantial type safety in modern development.
What do you think of these trends? How will they shape the way we code in 2025? Let me know!
👉 Check the full report.
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I have programmed in Java, C++, Javascript, TCL/tk, assembler for Intel 8031 microcontroller among some languages. I find Python like talking in english. I also measure it by the simplicity of the hello world program
print("Hello World")
I have used Python for my scripts for 12 years and for AI in Google Colab and Kaggle challenges.